Demand Forecasting for Executives and Professionals

This book surveys what executives who make decisions based on forecasts and professionals responsible for forecasts should know about forecasting. It discusses how individuals and firms should think about forecasting and guidelines for good practices. No prior knowledge is assumed in this book.

Autorentext

Dr. Bahman Rostami-Tabar is an Associate Professor in Data and Management Science, at Cardiff University, UK.

Dr. Stephan Kolassa is a Data Science Expert at SAP, Switzerland and Honorary Researcher at Lancaster University, UK. In 2023 Dr. Kolassa was named a Fellow of the International Institute of Forecasters.

Prof. Enno Siemsen is the Patrick A. Thiele Distinguished Chair in Business, University of Wisconsin-Madison, USA.

Inhalt

Part 1. Introduction 1. Introduction 2. The forecasting workflow 3. Choice under uncertainty 4. A simple example Part 2. Forecasting basics 5. Know your time series 6. Time series components 7. Time series decomposition Part 3. Forecasting models 8. Low hanging fruit: simple forecasts 9. Exponential Smoothing 10. ARIMA models 11. Causal models and predictors 12. Count data and intermittent demand 13. Forecasting hierarchies 14. Artificial Intelligence and Machine Learning 15. Long, multiple and non-periodic seasonal cycles 16. Human judgment Part 4. Forecasting quality 17. Error measures 18. Forecasting competitions Part 5. Forecasting organisation 19. Leading forecasters and forecasting teams 20. Sales and operations planning 21. Why does forecasting fail? Part 6. Learning More 22. Learning more