Towards an understanding of the role of business intelligence systems in organisational knowing

Abstract

Recent advances in information technology (IT), such as the advent of business intelligence (BI) systems, have increased the ability of organisations to collect and analyse data to support decisions. There is little focus to date, however, on how BI systems might play a role in organisational knowledge creation -in organisational knowing. We develop a conceptual framework of organisational knowing based on a synthesis of the literature, and use this as a framework to investigate how BI systems facilitate knowing in a case organisation. We identify two practices triggered by BI systems that distinguish them from prior applications of IT: the ability to initiate problem articulation and dialogue, and that of data selection (e.g. to address information needs of organisational decision makers at different managerial levels). This study provides empirical evidence of the performative outcome of BI systems in relation to organisational knowing through the practices of articulation and data selection. It provides a practice perspective on BI and focuses on the role of BI systems in organisational knowing thereby opening up a new departure for BI research that considers the implications of BI systems in organisations with actual practice in mind.

Transactive memory systems and Web 2.0 in knowledge sharing: A conceptual model based on activity theory and critical realism

“…Third, technology is not able to substitute human interactions, meetings and dialogue (Prieto & Easterby-Smith, 2006), and more recent studies assert that KMS cannot successfully enhance knowledge sharing without taking social and organisational aspects into account (Padova & Scarso, 2012). This limitation is even more strongly recognised from the practice-based perspective where KS is seen to be driven by social interactions (Newell & Galliers, 2006;Shollo & Galliers, 2016).…”

“…More recent studies suggest that such knowledge sharing could be supported with the use of interactive Web 2.0 tools (Wagner & Bolloju, 2005;Davison et al, 2013;Von Krogh, 2012), whose socially-driven and interactive features help overcome the limitations of the traditional ICT used in organisations (Kaiser et al, 2007;McAfee, 2006), and whose role is to facilitate action (Shollo & Galliers, 2016). However, the effect of Web 2.0 technologies on knowledge processes, and the impact of their implementation in organisations, are under-explored in IS research (Huang et al, 2015;Von Krogh, 2012).…”

Factors influencing business intelligence and analytics usage extent in South African organisations

“…Through the successful use of Business Intelligence and Analytics (BI&A), organisations can harvest and extract greater value from their data assets, thus more likely able to outperform their competitors (LaValle, Lesser, Shockley, Hopkins & Kruschwitz, 2011;Sidorova & Torres, 2015). Analysis of data through the use of BI&A tools and techniques allows organisations to gain insights into key areas to drive effective decision making (Chaudhuri, Dayal & Narasayya, 2011;Rouhani, Ashrafi, Zare & Afshari, 2016;Shollo & Galliers, 2015). LaValle et al (2011) concluded that higher performing organisations are twice as likely to use analytics whether it be for growth, efficiency or competitive advantage purposes.…”

“…The benefits of data-driven decision making are both improved productivity and market value, as was empirically shown in a study by Brynjolfsson, Hitt and Kim (2011) who concluded that organisations who adopted data-driven decision-making practices showed 5-6% higher productivity rates. BI&A practices and tools are seen as key enablers of data-driven decision making and provide the framework and support for organisations wanting to make better fact-based decisions (Davenport & Dyché, 2013;Shollo & Galliers, 2015;Wixom & Watson, 2010).…”

25+ Years of Business Intelligence and Analytics Minitrack at HICSS: A Text Mining Analysis

“…Based on extensive literature reviews, several authors focus on understanding, conceptualization and/or systematization of BI, see for example [6], [8], [24], [34] and [35]. Frequently, BI is differentiated into BIas-product, BI-as-a-process and BI-as-a-tool.…”