Contribution of Decision Support System in Enhancing Productivity and Profitability of the Firm

The business paradigms are changing amidst changing business environment. There are newer technologies at disposal, rising customer awareness and their expectations from the need to attain efficiency and effectiveness in business processes for survival and competitive advantage. This paper provides insights on the significance of business decision making and present state of organizations that are striving to achieve optimal utilization of limited business resources. The paper highlights the nature of linear programming model and its importance in effective business decision making. The business impact of model is illustrated in the case using the linear programming model and transportation method through excel solver in computer manufacturing firms to help in deciding optimum quantity to produce within limited resources and how the computers manufactured can be distributed to market places at minimal cost. The paper elicits the effectiveness of the linear programming model to realize good decision making in business by meeting the business objectives through optimal utilization of resources. It concludes that model driven decision support system enhances the productivity and profitability of the firm in a constrained environment and is a highly effective model for solving business problems

CONFLICT IDENTIFICATION AND RECONCILIATION IN A COLLABORATIVE MANUFACTURING SCHEDULING TASK

We studied the process of production scheduling in a large chemical plant. Scheduling in that environment is inherently a group process because multiple experts are needed to construct a schedule and to manage its execution. A mathematical formulation of the production scheduling problem yields a mixed-integer linear programming model too large to solve in a reasonable time with current technology. We therefore use an intelligent decision support system (DSS) to heuristically find a satisficing solution to the production scheduling problem. Our DSS is based on a model of the collaborative nature of the task, and it focuses on the communication, argumentation, and reconciliation strategies undertaken by individuals. Using actual production schedules, we show that our DSS can lead to measurable improvements over humanly-designed plans, where the quality of the schedule is measured using the objective function of the mathematical formulation of the problem.Artificial intelligence, decision support systems, intelligent agents, argumentation