Sensegiving in organizations via the use of business analytics

Abstract

PurposeBusiness analytics (BA) has been a breakthrough technological development in recent years. Although scholars have suggested several solutions in using these technologies to facilitate decision-making, there are as of yet limited studies on how analysts, in practice, improve decision makers' understanding of business environments. This study uses sensemaking theory and proposes a model of how data analysts generate analytical outcomes to improve decision makers' understanding of the business environment.Design/methodology/approachThis study employs an interpretive field study with thematic analysis. The authors conducted 32 interviews with data analysts and consultants in Australia and New Zealand. The authors then applied thematic analysis to the collected data.FindingsThe thematic analysis discovered four main sensegiving activities, including data integration, trustworthiness analysis, appropriateness analysis and alternative selection. The proposed model demonstrates how these activities support the properties of sensemaking and result in improved decision-making.Research limitations/implicationsThis study provides strong empirical evidence for the theory development and practice of sensemaking. It brings together two distinct fields – sensemaking and business analytics – and demonstrates how the approaches advocated by these two fields could improve analytics applications. The findings also propose theoretical implications for information system development (ISD).Practical implicationsThis study demonstrates how data analysts could use analytical tools and social mechanisms to improve decision makers' understanding of the business environment.Originality/valueThis study is the first known empirical study to conceptualize the theory of sensemaking in the context of BA and propose a model for analytical sensegiving in organizations.

Knowledge transfer: Graduates’ capability to demonstrate and produce business innovation

“…According to Saunders, Lewis and Thornhill (2016:136-137), pragmatism allows the study to explore what can work in the real world and determine whether graduates do possess the practical skills and knowledge to produce effective business innovation. A signification framework methodology was used for this research, which refers to the process of creating an underlying structure used for the representation of meaning that is generally applied in sensemaking, sensegiving, knowledge sharing, leadership, narrative and decision making (Deprez & Hanchar 2017;Magoma 2018;Namvar, Intezari & Im 2021). A signification framework is the basic structure underlying a system, concept, text or narrative (Du Toit 2003;Jakubik 2021;Snowden 2011).…”

Business analytics, corporate entrepreneurship, and open innovation

“…BA encompasses various programs, technologies, and techniques that enable businesses to collect, store, retrieve, and analyze diverse, large, and real data to generate valuable information. As Namvar et al. (2021) suggest, BA leads to better decision-making (Shamim et al.…”

“…BA encompasses various programs, technologies, and techniques that enable businesses to collect, store, retrieve, and analyze diverse, large, and real data to generate valuable information. As Namvar et al (2021) suggest, BA leads to better decision-making (Shamim et al, 2019), innovation, cost savings, and increased productivity. By leveraging real-time data on customer and competitor behavior, businesses can identify and pursue innovation opportunities with greater confidence and reduced risk, enhancing their practical ability to innovate (Côrte-Real et al, 2017).…”

Business analytics approach to artificial intelligence

“…Silva et al (2021) indicate that the term "Industry 4.0" has emerged to characterize various adoptions of Information and Communication Technologies (ICT) in production processes. Hence, business analytics (BA) is considered as a technological advancement that facilitates decision making (Namvar et al, 2021). Thus, business analytics facilitates data analysis and relates it to the use of emerging technologies, which enable the transformation of decision-making dynamics in organizations (Seufert and Schiefer, 2005;Ward et al, 2014).…”