Demand forecasting for job order products in highly technological and emerging industries
Demand forecasting is an important step of a company’s supply chain management process, allowing companies to project their needs for different components that are used in the final product. This is even more important in emerging industries with job order (or project-based) products where historica...
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ndltd-UTEXAS-oai-repositories.lib.utexas.edu-2152-ETD-UT-2012-05-55142015-09-20T17:09:03ZDemand forecasting for job order products in highly technological and emerging industriesMcFarland, Ian ChristopherDemand forecastingSupply chainDemand forecasting is an important step of a company’s supply chain management process, allowing companies to project their needs for different components that are used in the final product. This is even more important in emerging industries with job order (or project-based) products where historical demands do not exist and components may not be readily available or may involve a long lead time. Developing a demand forecasting model which accurately projects the needs of components for a company can decrease costs while decreasing overall lead times of final products. This demand forecast model takes into account projected component needs along with the likelihood of successfully winning a project bid. The model is extended to four different demand forecasting formulas incorporating different use of the winning probabilities. Historical results are then used to compare the methods and their advantages and disadvantages are discussed.text2012-08-16T18:27:59Z2012-08-16T18:27:59Z2012-052012-08-16May 20122012-08-16T18:28:06Zthesisapplication/pdfhttp://hdl.handle.net/2152/ETD-UT-2012-05-55142152/ETD-UT-2012-05-5514eng |
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English |
format |
Others
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Demand forecasting Supply chain |
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Demand forecasting Supply chain McFarland, Ian Christopher Demand forecasting for job order products in highly technological and emerging industries |
description |
Demand forecasting is an important step of a company’s supply chain management process, allowing companies to project their needs for different components that are used in the final product. This is even more important in emerging industries with job order (or project-based) products where historical demands do not exist and components may not be readily available or may involve a long lead time. Developing a demand forecasting model which accurately projects the needs of components for a company can decrease costs while decreasing overall lead times of final products. This demand forecast model takes into account projected component needs along with the likelihood of successfully winning a project bid. The model is extended to four different demand forecasting formulas incorporating different use of the winning probabilities. Historical results are then used to compare the methods and their advantages and disadvantages are discussed. === text |
author |
McFarland, Ian Christopher |
author_facet |
McFarland, Ian Christopher |
author_sort |
McFarland, Ian Christopher |
title |
Demand forecasting for job order products in highly technological and emerging industries |
title_short |
Demand forecasting for job order products in highly technological and emerging industries |
title_full |
Demand forecasting for job order products in highly technological and emerging industries |
title_fullStr |
Demand forecasting for job order products in highly technological and emerging industries |
title_full_unstemmed |
Demand forecasting for job order products in highly technological and emerging industries |
title_sort |
demand forecasting for job order products in highly technological and emerging industries |
publishDate |
2012 |
url |
http://hdl.handle.net/2152/ETD-UT-2012-05-5514 |
work_keys_str_mv |
AT mcfarlandianchristopher demandforecastingforjoborderproductsinhighlytechnologicalandemergingindustries |
_version_ |
1716822838915104768 |