Business Information Visualization for Decision-Making Support -- A Research Strategy

Abstract

In most management domains, problem-solving is overwhelming because of the large amount of complicated data, multiple complex relationships among data, and the negotiability of the constraints. Although computers become more and more available, the primary challenge of the computing society in the current and coming decades is not the computational power. It is the collected or generated data, especially their presentations to users in a comprehensible form, that affect and limit the basic capabilities of computing. It is extremely necessary to improve the communication between users and computers, to transform the vast computing-related data into some representations that help humans to understand the data. Humans are visual creatures. Most of what we learn comes through our sight. An effective solution to the challenge is to shift some of the user’s cognitive load to human perceptual systems by using computer-generated, domain-specific visualizations. Based on the previous research results in the development and the evaluation of a visualization-based decision support system for manufacturing production planners [Zhang 95], this research paper focuses on developing a research strategy for building visualizations of nongeometric data that are massive in both size and dimensionality to help decision makers to achieve data comprehension and eventually to improve problem-solving performance. The practice of business information visualization needs guidelines from theoretical perspectives, as well as practical perspectives. As business information visualization is an area where few theoretical and practical results have been obtained, we construct the visualization theory by expanding related work in other fields. We will then apply the visualization model to concrete business domains to verify the effectiveness of the model. We hope that a new discipline for business information visualization will be established and it will have its own theoretical foundation and methodology. As the visualization of large data sets is a problem of concern in many management domains, this research has both theoretical and practical contributions.