Data visualization in support of executive decision making

Abstract

Aim/Purpose This journal paper seeks to understand historical aspects of data management, leading to the current data issues faced by organizational executives in relation to big data and how best to present the information to circumvent big data challenges for executive strategic decision making. Background This journal paper seeks to understand what executives value in data visualiza-tion, based on the literature published from prior data studies. Methodology The qualitative methodology was used to understand the sentiments of execu-tives and data analysts using semi-structured interview techniques. Contribution The preliminary findings can provide practical knowledge for data visualization designers, but can also provide academics with knowledge to reflect on and use, specifically in relation to information systems (IS) that integrate human experi-ence with technology in more valuable and productive ways. Findings Preliminary results from interviews with executives and data analysts point to the relevance of understanding and effectively presenting the data source and the data journey, using the right data visualization technology to fit the nature of the data, creating an intuitive platform which enables collaboration and new-ness, the data presenter's ability to convey the data message and the alignment of the visualization to core the objectives as key criteria to be applied for suc-cessful data visualizations Recommendations for Practitioners Practitioners, specifically data analysts, should consider the results highlighted in the findings and adopt such recommendations when presenting data visualiza-tions. These include data and premise understanding, ensuring alignment to the executive's objective, possessing the ability to convey messages succinctly and clearly to the audience, having knowledge of the domain to answer questions effectively, and using the right technology to convey the message. Recommendation for Researchers The importance of human cognitive and sensory processes and its impact in IS development is paramount. More focus can be placed on the psychological fac-tors of technology acceptance. The current TAM model, used to describe use, identifies perceived usefulness and perceived ease-of-use as the primary consid- erations in technology adoption. However, factors that have been identified that impact on use do not express the importance of cognitive processes in technol-ogy adoption. Future Research Future research requires further focus on intangible and psychological factors that could affect technology adoption and use, as well as understanding data visualization effectiveness in corporate environments, not only predominantly within the Health sector. Lessons from Health sector studies in data visualiza-tion should be used as a platform.