000			02128nam a22001937a 4500
005			20250306154058.0
008			250305b2024 |||||||| |||| 00| 0 eng d
020			_a9781032507729
082			_a330.0112 KOL-S
100			_aKolassa, Stephan
245			_aDemand forecasting for executives and professionals / _cStephan Kolassa, Bahman Rostami-Tabar and Enno Siemsen
260			_aBoca Raton _bCRC Press _c2024
300			_a254p.
500			_aThis 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. It introduces readers to the subject of time series, presents basic and advanced forecasting models, from exponential smoothing across ARIMA to modern Machine Learning methods, and examines human judgment's role in interpreting numbers and identifying forecasting errors and how it should be integrated into organizations. This is a great book to start learning about forecasting if you are new to the area or have some preliminary exposure to forecasting. Whether you are a practitioner, either in a role managing a forecasting team or at operationally involved in demand planning, a software designer, a student or an academic teaching business analytics, operational research, or operations management courses, the book can inspire you to rethink demand forecasting. No prior knowledge of higher mathematics, statistics, operations research, or forecasting is assumed in this book. It is designed to serve as a first introduction to the non-expert who needs to be familiar with the broad outlines of forecasting without specializing in it. This may include a manager overseeing a forecasting group, or a student enrolled in an MBA program, an executive education course, or programs not specialising in analytics. Worked examples accompany the key formulae to show how they can be implemented
650			_aEconomic forecasting
650			_aDecision Making
700			_aRostami-Tabar, Bahman
700			_aSiemsen, Enno
999			_c93211 _d93211