CCE Theses and Dissertations

Successful Implementation of Decision Support Systems for Supply Chain Management within Manufacturing Companies

Date of Award

2005

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Graduate School of Computer and Information Sciences

Advisor

Sumitra Mukherjee

Committee Member

William L. Hafner

Committee Member

Maxine S. Cohen

Abstract

Decision Support Systems (DSS) development and implementation is a challenge that most manufacturing companies find difficult. However, implementing these complex systems is becoming more of a necessity to stay competitive in today's global economy. This paper reports on an in-depth empirical study of development/Implementation strategies commonly used in DSS and Enterprise Resource Planning (ERP) systems projects to promote success. The goal of the research was to determine which strategies promote success on DSS projects designed to enable supply chain management (SCM).

Through a survey of 80 industry professionals, the Study establishes that there are strategies that should be utilized based on system type. DSS users must have strong analytical skills. They must be able to analyze, interpret, and act on complex data. These analytical skills were found to be significantly more important for DSS users to have than ERP users (p < 0.05). Intelligent SCM systems must include "what if' functionality and allow users to evaluate multiple business scenarios before acting. The "small releases" systems development methodology (i.e., phased approach to implementing business functionality was found to be more appropriate for DSS than ERP projects (p < 0.05).

Many strategies, which are traditionally considered administrative in nature, were found to be more important for ERP systems projects (p< 0.05). Utilizing cross-functional project teams, ensuring user participation, securing top-management support, and providing extensive user training were all found to be significantly more important for ERP (p

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