Image Construction Rules for Visualizing the Non - Visual Managerial Data

Data representations and their impact on decision making performance have been a subject of Information Systems research for a long time [Benbasat et al. 86, DeSanctis 84, DeSanctis & Jarvenpaa 89, Vessey 91]. The graphical representations in most studies in this area are common business charts, such as pie, line, bar, among others. These charts are not necessarily designed to support any specific decision tasks or processes. Thus the focus of these studies has been limited to simple decision tasks with small data volume and simple data relationships. To date, visualization of large-amount, multi-dimensional managerial data for decision-making support is nearly nonexistent. Most existing visualization tools, such as IBM Data Explorer, AVS, and IRIS Explorer, are designed for scientific visualization purposes and are very difficult to use for visualizing managerial data. Considering the manufacturing production planning problems at the Electronic Card Assembly and Test plant (ECAT) at IBM Austin, Texas, the presented research studied the characteristics of the managerial data, then developed special visualization techniques for constructing visual representations to support planners to develop superior production plans. A visualization prototype VIZ_planner was designed and implemented, and empirically evaluated [Zhang 95]. Hundreds of products, thousands of components, and many other factors can be visualized to provide planners with production planning insight.