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Verlag: Auckland University Press, 1995
ISBN 10: 1869401239 ISBN 13: 9781869401238
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In den WarenkorbSoft cover. Zustand: Very Good. very good reading copy. immediate despatch from the uk 6 days a week.
Sprache: Englisch
Verlag: LAP Lambert Academic Publishing, 2010
ISBN 10: 3838323483 ISBN 13: 9783838323480
Anbieter: preigu, Osnabrück, Deutschland
Taschenbuch. Zustand: Neu. Sales Forecasting with SAP Enterprise Resource Planning | An Empirical Study | Peter Catt | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783838323480 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Sprache: Englisch
Verlag: LAP Lambert Academic Publishing, 2009
ISBN 10: 3838323483 ISBN 13: 9783838323480
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In den WarenkorbPaperback. Zustand: Brand New. 172 pages. 8.66x5.91x0.39 inches. In Stock.
Sprache: Englisch
Verlag: LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838323483 ISBN 13: 9783838323480
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In den WarenkorbZustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Catt PeterDr Peter Catt is a Supply Chain Solution Manager with Soltius New Zealand Limited. Peter holds a Doctor of Computing degree, an MBA and a Diploma in Industrial Production. Peter is also a member of the International Institu.
Sprache: Englisch
Verlag: LAP Lambert Academic Publishing, 2010
ISBN 10: 3838323483 ISBN 13: 9783838323480
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The sales forecasting accuracy of Enterprise Resource Planning (ERP) systems can have a significant impact on business profitability. However, commonly adopted measures of forecast accuracy, such as mean absolute error (MAE) and mean absolute percentage error (MAPE), do not provide explicit costs associated with forecast errors. This abridged doctoral thesis adopts a quantitative case study methodology to evaluate the nine forecasting models (2 moving average and 7 exponential smoothing) of SAP's enterprise resource planning system (SAP® ERP 6.0). The SAP forecast models are evaluated against both common statistical measures and newly developed commercial measures of forecast error. Although not intended as a training manual or configuration guide, this work clearly explains and comprehensively reviews SAP's ERP forecasting functionality with the SAP professional in mind.