Visualisation of data in management accounting reports

Purpose – Managers are confronted with increasing information overload and growing pressure for effective and efficient decision making. The visualisation of data represents a way to overcome this dilemma and to improve management decision quality. The purpose of this paper is to transfer insights from visualisation research to the managerial accounting context and clarify the impact of visualisation on management accounting reports and decision making. The authors deduce implications for behavioural management accounting research, teaching, and business practice from previous findings and the results. Design/methodology/approach – The authors conducted an experiment with students and experienced managers. Participants had to evaluate eight different business units based on four accounts (sales, EBIT, FPY, and delivery reliability). The information the authors provided to the participants was either presented as tables only, or in tables and graphs. Findings – The empirical results show that supplementary graphs improve decision quality, especially within the manager sample but do not affect decision confidence in a performance evaluation task. The authors furthermore find that managers perform poorly when only provided with tables, and they achieve the overall best score when provided with both tables and graphs, whereas students perform similarly in both conditions. The authors additionally show that proficiency affects not only decision quality but also decision confidence. Research limitations/implications – The results differ from predictions based solely on the cognitive fit model, as the authors found differences in decision quality to be stronger within the group of managers. The cognitive fit model proposes that decision making performance will improve when the problem representation and the decision making task match. Applying the model to a management context, it is obviously insufficient to explain the differences the authors obtained in the experiment. The authors observed that proficiency plays a role in such performance evaluation tasks. Practical implications – Based on the results, management accountants should analyse the task that needs to be solved with the reported data. By analysing the type of task, accountants can derive the information processing strategy that will most likely be used by executives for problem solving and determine the suitable visualisation format based on the cognitive fit model. Moderate or complex monitoring tasks will presumably be accessed with perceptual information processing. Data should thus be visualised with graphs. Originality/value – The authors provide empirical evidence that supplementary graphs in management reports improve decision quality but not decision confidence. The authors furthermore illustrate the limits of the explaining power of the cognitive fit model in a management report context. In an extension of cognitive fit theory, the authors argue that proficiency plays a crucial role in performance evaluation tasks. The authors propose a process for visualisation of management reports based on their findings and previous findings.