Linking Business Analytics to Decision Making Effectiveness: A Path Model Analysis

Abstract

While business analytics is being increasingly used to gain data-driven insights to support decision-making, little research exists regarding the mechanism through which business analytics can be used to improve decision-making effectiveness at the organisational level. Drawing on the information processing view and contingency theory, this paper develops a research model linking business analytics to organisational decision-making effectiveness. The research model is tested using structural equation modelling based on 740 responses collected from UK businesses. The key findings demonstrate that business analytics, through the mediation of a data-driven environment, positively influences information processing capabilities, which in turn have a positive effect on decision-making effectiveness. The findings also demonstrate that the paths from business analytics to decision-making effectiveness have no statistical differences between large and medium companies but some differences between manufacturing and professional service industries. Our findings contribute to the business analytics literature by providing useful insights into business analytics applications and the facilitation of data-driven decision-making. They also contribute to managers' knowledge and understanding by demonstrating how business analytics should be implemented to improve decision-making effectiveness.

Theoretical Aspect In Formulating Assesment Model Of Big Data Analytics Environment

“…The components of organizational di-mension are including big data analytics strategy, top management support, resource commitment and organizational relationship [2][3][4][5][6][7]. Meanwhile, the people components are consisting of the analytics skills, managerial skills and analytics cultures [6][7][8].…”

How do top- and bottom-performing companies differ in using business analytics?

“…BA is seen to offer the possibilities for companies to be more effective at making strategic decisions (Cao et al 2015), improving organizational performance (Bronzo et al 2013), and creating competitive advantages (Davenport and Harris 2007). Four consecutive large scale questionnaire surveys have consistently showed that companies that use BA perform better than those that do not (Kiron and Shockley 2011;Lavalle et al 2011;Kiron et al 2012cKiron et al , 2014.…”

Barriers to Predictive Analytics Use for Policy Decision-Making Effectiveness in Turbulent Times: A Case Study of Fukushima Nuclear Accident

“…While it is not about predictive analytics use, a survey research draws on the information processing view and contingency theory to examine the effect of (descriptive) business analytics use on decisionmaking effectiveness at the organizational level [10]. Structural equation modeling analysis found that business analytics use positively influences information processing capability in data-driven decision environments.…”

“…In the private sector, which faces not only turbulent but also competitive decision environments, big data, business intelligence, and business analytics have been increasingly adopted and used to enhance organizational, analytical capabilities such as organizational memory, information integration, insight creation and visual presentation [43], managerial decision-making effectiveness [10], organizational performance [30,44], and supply chain performance [51,56]. In contrast, while the use of big data [21], business intelligence, and business analytics tools by large-size local governments in the U.S. has been studied for enhanced public services in the e-government field [13], there remains a relative lack of knowledge and understanding about effective business analytics use in a policy decision-making context in turbulent times.…”