Bačić et al. Business Information Visualization: A Visual Intelligence-Based Framework Proceedings of the Nineteenth Americas Conference on Information Systems, Chicago, Illinois, August 15-17, 2013. 1 Business Information Visualization: A Visual Intelligence- Based Framework  Dinko Bačić Cleveland State University Monte Ahuja College of Business Department of Computer and Information Science d.bacic@csuohio.edu Adam Fadlalla Qatar University College of Business and Economics Department of Accounting and Information Systems fadlalla@qu.edu.qa ABSTRACT Business Intelligence aims to improve decision quality. Research on BI achieving this goal is inconclusive, yet BI is still one of the top priorities among CIOs and is an active IS research area. A better understanding of the relationship between human intelligence and BI capabilities may lead to more fruitful BI endeavors. This paper proposes a conceptual framework that links capabilities of Business Information Visualization, a key modern BI enabler, to non-verbal (visual) intelligence abilities, and suggests propositional guidelines of how BI could improve decision making by impacting these intelligence abilities. The paper demonstrates that there is strong research support to suggest such linkages. Better understanding of what human abilities are important for better decisions, and what specific BI capabilities are needed to support these abilities will help improve the design, deployment, and utilization of BI tools, and, hopefully ultimately, achieve more efficient and effective business decisions. Keywords Business Information Visualization, Visual Intelligence, Business Intelligence, Decision Performance INTRODUCTION Business Information Visualization (BIV), a BI technology capability of displaying business information visually (Tegarden 1999) is gaining increasing attention with practitioners and researchers (Zhang 2001). In a quest to respond to recent ‘visualization fashion’, vendors are providing rich visualization capabilities fast, yet the users of BI systems often lack proper training in appropriate use of available graphical solutions and options (such as color, shape, formatting, labeling, etc)(Few 2004). As a result, many BI reporting solutions are enabling deployment of ‘chartjunk’ – “visual elements in charts and graphs that are not necessary to comprehend the information represented on the graph, or that distract the viewer from this information” (Tufte 1983). Instead of aiding and leveraging human cognitive and nonverbal abilities to reduce information complexity and uncertainty (Zack 2007), BI systems often deploy reporting solution that, at best, increase effort and cognitive load, and at worst, unnecessary increase complexity and uncertainty or even mislead decision makers (Few 2004; Tufte 1983; Tufte 1990; Tufte 1997; Ware 2000). Our research suggests that in order improve the support and effectiveness of decision making, BI and its BIV capabilities need to assist human abilities and visual intelligence potential as a way of reducing information complexity and uncertainty. By enhancing and enabling human visual intelligence abilities and processes, BI will more effectively achieve its supreme goal of assisting in decision making. More specifically, the paper provides a formal framework that links BI visualization capabilities to human visual intelligence abilities and outlines propositions for future research. The paper offers three key contributions. First, a novel intelligence-based framework for assessing Business Information Visualization effectiveness is introduced. Second, key Information Visualization and BIV literature is identified and aligned CORE Metadata, citation and similar papers at core.ac.uk Provided by AIS Electronic Library (AISeL)