Academic journal article Issues in Informing Science & Information Technology

Factors Driving Business Intelligence Culture

Academic journal article Issues in Informing Science & Information Technology

Factors Driving Business Intelligence Culture

Article excerpt

Introduction

The continuing growth of business intelligence (BI) applications and related issues keeps drawing significant attention of researchers and practitioners, and the variety of BI forms has introduced numerous innovations, definitions and redefinitions in areas relating to business intelligence. There have been suggestions to separate internal intelligence from external intelligence (Nash, 2010), business intelligence from business analytics, position decision support systems (DSS) as a part of BI (Kopackova & Skrobackova, 2006) or BI as a part of decision support (Power, 2013); a rather detailed genealogy of the DSS field, including relations between DSS and BI, is presented in Arnott and Pervan (2014). This set of discussions has significantly widened the field of BI innovations and applications. However, regardless the quest of BI for advanced informing, the low levels of BI adoption are a fact confirmed by many academic and practical sources, and numerous reasons have been named to understand the contradictory set of factors that drive BI success or failure. The technical foundations of BI are based on contemporary information technologies, and some researchers place IT as a dommating factor--e.g., Cao and Duang (2014) state that "business intelligence and business analytics are based on sophisticated information technologies". However, human factors of BI adoption have always been quoted by researchers as equally, if not more, important than technology factors. All steps of the BI cycle actually are performed by users, and BI technology is just an environment that accumulates and translates human intents without automating them--it does not create strategies, formulas or control signals.

Marchand, Kettinger, and Rollins (2001) have pointed to the importance of human factors like information behaviors and values. Fleisher (2008) has named creativity and original thinking among important human factors. Presthus (2014) has defined BI systems as socio-technical systems with equal importance between technical and human factors. Yeoh and Popovic (2015) have pointed out to user-oriented change management. Yoon, Ghosh, and Jeong (2014) have stressed social influence and learning climate as important human factors in adopting BI. Cohen and Levinthal (1990) have suggested an approach to merging managerial and informational factors into a feature named the absorptive capacity of an organization to receive and use external information, and stated that organizational absorptive capacity is not only the sum of individual capacities, but also the organized ability to exploit them. Carlo, Lyytinen, and Boland (2012) defined the existence of collective mindfulness as a set of mindful behaviors that create awareness and facilitate discovery in high risk environments.

The existence of a set of important human factors, pointed out in the above research as well as many other sources, suggests the presence of business intelligence culture as a collection of, attitudes, norms, and values which joins together the human traits of business intelligence. The principal challenges in implementing BI projects, pointed out in various research and professional sources (Gartner Research, 2008), are as well closely related to human factors, especially addressing BI culture aspects (see Table 1).

One of the most significant features of the above challenges is that many business organizations having undertaken BI projects did not give the human factors required attention and had ended up with a fragmented implementation of BI or not using the technology at all.

The analysis of recent research in the field of BI adoption has shown several driving forces considered important for the successful adoption of BI (this set is by no means exhaustive): data-driven approaches, BI agility, BI maturity, and BI acceptance. This paper aims at the analysis of the research sources regarding the above forces to subsequently point out the importance of the factors influencing BI culture and define a set of such factors. …

Search by... Author
Show... All Results Primary Sources Peer-reviewed

Oops!

An unknown error has occurred. Please click the button below to reload the page. If the problem persists, please try again in a little while.