Collaborative decision making for supply network decisions
Abstract
Supply network decision making process is very critical in the management of operational processes. The many types of decisions and number of people involved in the process create complex environments. The collaborative integration of different decision support system models facilitates knowledge extraction of several key elements of the operation. In the development and implementation of a promotional activity, decisions on purchasing and production quantities are required to achieve optimal inventory and fulfillment rate levels. A promotional forecasting model is developed that calculates the impact on demand of price due to price promotions and ordering quantities of raw material. This serves as input information for other decision support system models such as supplier selection procedure and direct/indirect delivery percent calculation. A collaborative approach integrates these three decision support systems and defines a decision protocol. This collaborative approach focuses on the application of a knowledge-based system to implement the use of `best practices'. Experimental simulations using MERP software, study the influence of collaborative decision making processes on the performance of the manufacturing organization. Parameters on price promotions, lead-time, production and purchasing policies, and planning frequencies were studied. Results conclude that a dynamic collaborative decision making approach optimizes the utility function, 18% higher than the best performance from independent decision support systems applications.
Degree
M.S.I.E.
Advisors
Nof, Purdue University.
Subject Area
Marketing|Industrial engineering|Operations research
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