Optimizing Order Promising
Author(s)
Li, Zhipeng (Zhipeng Simon)
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Alternative title
OOP
Other Contributors
Massachusetts Institute of Technology. Engineering Systems Division.
Advisor
Lawrence Lapide.
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Online purchasing is now popular following the growth of E-business. Retailers ordering online will get the exact delivery date of goods for their better management of sales operations. Suppliers should keep their competence at order promising to attract customers in the market filled with increasing competition. Generally Order Promising means that the supplier receiving an order should determine to accept the order or not. If accepted, then the supplier should determine the delivery date. Necessary data should be replied to the ordering customer. Optimizing Order Promising (OOP) is Order Promising (OP) that is optimized. This thesis probed into OP and OOP and summarized the characteristics and differences of the current OP software products on the basis of interviews and the investigation into the existing OP software suppliers - i2 Technologies, Oracle and SAP. Backed by the thorough analysis on a particular case study company, this thesis discusses the workflow and model of OOP by combining the author's own thoughts on improving existing OP workflows. A company can add many new functions to the OOP model designed in this thesis on the basis of the appropriate adjustments to the existing OP workflows and systems. (cont.) For example, different customers can be managed in a classified way in accordance with historical sales; customer trust can be increased by the approach of Customer Allocation; every deal of the company can be guaranteed to be profitable; and no negligence to important customers will occur due to favoring unimportant customers. Moreover, in dealing with the disruptions that have frequently occurred these years, the thesis designed the order promising process dealing with emergencies for the manufacturers of public utilities, ensuring that a company will implement their social responsibility while harvesting profits.
Description
Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2007. Includes bibliographical references (leaves 86-89).
Date issued
2007Department
Massachusetts Institute of Technology. Engineering Systems DivisionPublisher
Massachusetts Institute of Technology
Keywords
Engineering Systems Division.