03009nam 2200661 450 991013742480332120200520144314.01-119-22829-81-119-22827-1(CKB)3710000000539123(EBL)4206560(SSID)ssj0001592694(PQKBManifestationID)16289788(PQKBTitleCode)TC0001592694(PQKBWorkID)14880583(PQKB)10465819(PQKBManifestationID)16294802(PQKB)21178385(DLC) 2015046278(Au-PeEL)EBL4206560(CaPaEBR)ebr11136243(CaONFJC)MIL881818(OCoLC)930364177(CaSebORM)9781119224563(MiAaPQ)EBC4206560(EXLCZ)99371000000053912320160115h20152015 uy 0engur|n|---|||||txtccrBusiness forecasting practical problems and solutions /edited by Michael Gilliland, Udo Sglavo, Len Tashman1st editionHoboken, New Jersey :Wiley,2015.©20151 online resource (442 p.)Wiley and SAS Business SeriesDescription based upon print version of record.1-119-24459-5 1-119-22456-X Includes bibliographical references at the end of each chapters and index."This title provides many of the most important and though-provoking articles by the leading business forecasting practitioners and academics. It exposes the reader to many of the best minds (and most provocative ideas) in the forecasting profession, with thorough referencing to related material for further reading. It provides: - A critical look at many of the vexing problems in business forecasting, such as volatility, forecastability, performance metrics, and human interaction in the forecasting process. - Introduces emerging new approaches such as combining data mining with forecasting and aggregating/reconciling across time hierarchies. - Addresses the often overlooked topic of data preparation and data quality (part of the "pre-processing" of data prior to forecasting. - Covers the proven (yet rarely used) method of combining forecasts to improve accuracy. Contains a mix of more formal/rigorous pieces, with brief chapters (adapted from blog posts) dealing narrowly with very specific topics"--Provided by publisher.Wiley and SAS business series.Business forecastingBusiness forecasting.658.4/0355BUS086000bisacshGilliland MichaelSglavo Udo1968-Tashman Len1942-MiAaPQMiAaPQMiAaPQBOOK9910137424803321Business forecasting2020035UNINA