The Practical Use of BI Visualizations in Decision-making

Abstract

Background and problem: Due to the constantly altering business environment, firms are trying to find ways of combining information technology (IT) and decision-making in order to grasp information of the complex and dynamic business environment. As a solution to this strenuousness; business intelligence (BI) systems serve to conduct more efficient and reliable decisions by the means of visualizations. One existing gap in the research of BI concerns the socio-technical effects involved in the decision-making, in which knowledge of how BI visualizations are used and may be used in practice to support the decision-making have remained limited. Research aim: The research aim of the study is to investigate how BI visualizations are and may be used to support strategic and operational decisions. Further, the study addresses how BI visualizations are used in various decision contexts. Research questions: The following questions are addressed in order to achieve the research aim: (1) How are and may BI visualizations be used in strategic and operational decisions? (1a) Which visual elements are used depending on the task and decision category? (2) How are BI visualizations used in different decision contexts? Research design: A qualitative study was made through semi-structured interviews. In-depth interviews with six people from the purchasing company were conducted in order to understand how BI and visualizations are and may be used. Two people from the consultancy company were interviewed in order to understand how BI and visualizations may be used. Discussion and conclusion: The primary purpose of BI systems in the purchasing company is to support decision-making from a strategic perspective by providing the business with new insights and monitor business processes. However, the findings in this study also suggest that BI visualizations are used for operational errands. Strategic decisions are primary based on graphical representations, whereas operational decisions are based on data derived from tables and additional calculations in Excel. By creating more interactive, initiative, and humanizing visualizations, the end-users may discover new patterns of information and enhance the cognitive fit without being overwhelmed by data. BI visualizations may also be used in a larger extent to detect errors in data. The usage depends on the decision situation, in which decisions made in the fact-based contexts domains tend to be based on intuitions and BI visualizations, before responding to the business problem. This differs from the pattern-based management domains, in which actions are done prior to the analysis as there is lack of data. Further the findings indicate that several people are often involved in the decisions. The mental model of the respondents is not entirely fit in a cognitive aspect.