2026-09-21T07:57:32Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/348442022-01-28T18:15:53Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Donald B. Rosenfield and Jérémie Gallien.
Cheung, Christine
Leaders for Manufacturing Program.
Leaders for Manufacturing Program at MIT
Massachusetts Institute of Technology. Department of Chemical Engineering
Sloan School of Management
2006-11-08T16:48:08Z
2006-11-08T16:48:08Z
2005
2005
http://hdl.handle.net/1721.1/34844
63199379
Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering; in conjunction with the Leaders for Manufacturing Program at MIT, 2005.
Includes bibliographical references (p. 75-76).
Companies like Procter & Gamble that operate on a make-to-stock strategy use forecasts to drive their manufacturing, selling, and buying processes. Because forecasting future demand is not an exact science, inventory management models have been developed to accommodate these uncertainties. There has been a significant improvement in inventory management of base products, where forecasts are based on historical sales information. Because the bulk of forecasting methods depend on this use of historical data, little effort to date has been focused on inventory management of a new product. The use of traditional time- series forecasting methods is not realistic and companies typically resort to using judgmental or analogous (e.g. curve-fitting) means, which are less applicable in making short-range production and inventory decisions. The lack of a new product forecasting method poses a significant problem in the cosmetic industry, which faces an increasing dependence on the introduction of new products for sales growth. Inventory and supply chain management is made even more difficult by the short product-life cycle, long lead times, and complexity and number of SKUs. As the industry trends toward increasing the pace of new product launches, forecast accuracy of a new product in its initial launch stages becomes more critical to manage the supply network's inventory and capacity. This document outlines a supply strategy for new product introductions that improves information management in the forecasting process to optimize supply and inventory planning.
(cont.) This method is designed to improve product pipeline forecasts as well as basic replenishment forecasts in the first few months of a product's launch. The model was tested and validated by historical simulations on a cosmetic product line. Results showed significant inventory reductions compared to current inventory management policies.
by Christine Cheung.
S.M.
M.B.A.
76 p.
3928460 bytes
3931566 bytes
application/pdf
application/pdf
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Sloan School of Management.
Chemical Engineering.
Leaders for Manufacturing Program.
A short-range forecasting and inventory strategy for new product launches
Thesis
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<Abstract>Companies like Procter & Gamble that operate on a make-to-stock strategy use forecasts to drive their manufacturing, selling, and buying processes. Because forecasting future demand is not an exact science, inventory management models have been developed to accommodate these uncertainties. There has been a significant improvement in inventory management of base products, where forecasts are based on historical sales information. Because the bulk of forecasting methods depend on this use of historical data, little effort to date has been focused on inventory management of a new product. The use of traditional time- series forecasting methods is not realistic and companies typically resort to using judgmental or analogous (e.g. curve-fitting) means, which are less applicable in making short-range production and inventory decisions. The lack of a new product forecasting method poses a significant problem in the cosmetic industry, which faces an increasing dependence on the introduction of new products for sales growth. Inventory and supply chain management is made even more difficult by the short product-life cycle, long lead times, and complexity and number of SKUs. As the industry trends toward increasing the pace of new product launches, forecast accuracy of a new product in its initial launch stages becomes more critical to manage the supply network's inventory and capacity. This document outlines a supply strategy for new product introductions that improves information management in the forecasting process to optimize supply and inventory planning.</Abstract>
<Abstract>(cont.) This method is designed to improve product pipeline forecasts as well as basic replenishment forecasts in the first few months of a product's launch. The model was tested and validated by historical simulations on a cosmetic product line. Results showed significant inventory reductions compared to current inventory management policies.</Abstract>
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