Storytelling, business analytics and big data interpretation

Abstract

Purpose The purpose of this paper is to explore the role of storytelling in data interpretation, decision-making and individual-level adoption of business analytics (BA). Design/methodology/approach Existing theory is extended by introducing the concept of BA data-driven storytelling and by synthesizing insights from BA, storytelling, behavioral research, linguistics, psychology and neuroscience. Using theory-building methodology, a model with propositions is introduced to demonstrate the relationship between storytelling, data interpretation quality, decision-making quality, intention to use BA and actual BA use. Findings BA data-driven storytelling is a narrative sensemaking heuristic positively influencing human behavior towards BA use. Organizations deliberately disseminating BA data-driven stories can improve the quality of individual data interpretation and decision-making, resulting in increased individual utilization of BA on a daily basis. Research limitations/implications To acquire a deeper understanding of BA data-driven storytelling in behavioral operational research (BOR), future studies should test the theoretical model of this study and focus on exploring the complexity and diversity in individual attitudes toward BA. Practical implications This study provides practical guidance for business practitioners who struggle with interpreting vast amounts of complex data, making data-driven decisions and incorporating BA into daily operations. Originality/value This cross-disciplinary study develops existing BOR, storytelling and BA literature by showing how a novel BA data-driven storytelling approach can facilitate BA adoption in organizations.

An Empirical Examination of the Relationship Between Data Storytelling Competency and Business Performance

“…In the context of business analytics, Boldosova and Luoto (2019) describe data storytelling as a narrative sensemaking heuristic that helps business analytics practitioners to make sense of the big data and guides them though the process of interpreting and translating complex data patterns into a sequence of coherent and meaningful insights, which in turn, can lead to improved decision-making and performance. Similarly, Dykes (2019) defines data storytelling as a structured approach for conveying and communicating insights resulting from the data analysis process in a way that allows the relevant audience to easily and quickly understand the analytical insights, understand the context of these insights, and draw conclusions from them.…”

“…Another study by Boldosova (2019) found that the use of data storytelling in combination with big data analytics techniques can improve customers' adoption of services and products and enhance the relationship between organizations and their customers, thereby developing innovative solutions to meet growing market needs and enhancing existing business processes. Recent studies have also emphasized the pivotal role that data storytelling plays in augmenting business analytics initiatives and assisting individuals in interpreting and making sense of complex data patterns and insights (Boldosova & Luoto, 2019). Sharda, Delen, and Turban (2019) argue that when insights generated from business analytics are integrated into compelling stories, organizations can see a marked change in their performance across key areas of the business, such as return on investment (ROI), return on sales (ROS), customer retention and satisfaction, employees' productivity, employees' growth and professional development, and market share (Aydiner, Tatoglu, Bayraktar, Zaim, & Delen, 2019).…”

“…Several conceptual studies suggest that the adoption of data storytelling in business analytics practices can contribute positively to business performance by enabling effective and timely data-driven decision-making (e.g., Damodaran, 2017;Davenport & Kim, 2013;Dessart, 2018;Dykes, 2019;Hedman et al, 2018;Herschel & Clements, 2017;Sundin et al, 2018;Vora, 2019). Building on these studies and considering how decision-making quality can mediate the relationship between data storytelling competency and business performance, the conceptual model developed by Boldosova and Luoto (2019) is particularly interesting as it postulates that the effective and appropriate use of data storytelling, resulting from the combined result of business analytics and data-driven environment, is positively related to decision-making quality. Boldosova and Luoto (2019) argue that the purpose of data storytelling is to guide the business analytics user through the process of interpreting and translating big data into valuable business insights, which in turn, can lead to improved decision-making quality and business performance.…”

“…Building on these studies and considering how decision-making quality can mediate the relationship between data storytelling competency and business performance, the conceptual model developed by Boldosova and Luoto (2019) is particularly interesting as it postulates that the effective and appropriate use of data storytelling, resulting from the combined result of business analytics and data-driven environment, is positively related to decision-making quality. Boldosova and Luoto (2019) argue that the purpose of data storytelling is to guide the business analytics user through the process of interpreting and translating big data into valuable business insights, which in turn, can lead to improved decision-making quality and business performance. In enterprise scenarios where business analytics insights (often presented in reports, dashboards, and predictive models) have to be delivered to business stakeholders, data storytelling provides an effective means to illustrate, step-bystep, the use of business analytics to generate actionable insights; understanding the business problem it solves; and making evidence-based decisions that provide a solution to the business problem and ultimately lead to improvements in business processes and outcomes.…”

“…This study mainly contributes to the limited body of empirical research linking data storytelling and business performance by developing a mediation model that not only shows a positive relationship between data storytelling competency and business performance, but this relationship can also be significantly mediated by decision-making quality. While conceptual research on data storytelling (Boldosova & Luoto, 2019;Elias et al, 2013;Herschel & Clements, 2017) generally suggests that data storytelling capabilities can help improving decision-making quality and business performance, such a belief has rarely been examined based on testable hypotheses underpinned by theories. The findings from this study make an original contribution to the data storytelling literature by providing an explanation for, and new insights into, how data storytelling competency creates a strategic value for business analytics practices and the resulting business decisions and performance.…”