Demand Forecasting for Inventory Control (Hardcover, 2015 ed.)

This book describes the methods used to forecast the demands at inventory holding locations. The methods are proven, practical and doable for most applications, and pertain to demand patterns that are horizontal, trending, seasonal, promotion and multi-sku. The forecasting methods include regression, moving averages, discounting, smoothing, two-stage forecasts, dampening forecasts, advance demand forecasts, initial forecasts, all time forecasts, top-down, bottom-up, raw and integer forecasts, Also described are demand history, demand profile, forecast error, coefficient of variation, forecast sensitivity and filtering outliers. The book shows how the forecasts with the standard normal, partial normal and truncated normal distributions are used to generate the safety stock for the availability and the percent fill customer service methods. The material presents topics that people want and should know in the work place. The presentation is easy to read for students and practitioners; there is little need to delve into difficult mathematical relationships, and numerical examples are presented throughout to guide the reader on applications. Practitioners will be able to apply the methods learned to the systems in their locations, and the typical worker will want the book on their bookshelf for reference. The potential market is vast. It includes everyone in professional organizations like APICS, DSI and INFORMS; MBA graduates, people in industry, and students in management science, business and industrial engineering.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Release date:	December 2014
First published:	2015
Authors:	Nick T. Thomopoulos
Dimensions:	235 x 155 x 17mm (L x W x T)
Format:	Hardcover
Pages:	183
Edition:	2015 ed.
ISBN-13:	978-3-319-11975-5
Categories:	Books > Business & Economics > Business & management > Management of specific areas > Distribution & warehousing management Promotions
LSN:	3-319-11975-3
Barcode:	9783319119755

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