Enhancing Business-Intelligence Tools with Value-Driven Recommendations

Adir Even, Yoav Kolodner, Roy Varshavsky

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Business-intelligence (BI) tools are broadly adopted in organizations today, supporting activities such as data analysis, decision making, and performance measurement. This study investigates the integration of feedback and recommendation mechanisms (FRM) into BI tool, defining FRM as visual
cues that are embedded into the tools and provide the end-user with usage guidelines. The study focuses on FRM that are based on assessment of previous usage. It introduces the concept of valuedriven usage metadata - a novel methodology for tracking and communicating the usage of data resources, linked to a quantitative assessment of the value gained. A laboratory experiment tested FRM-integration with 200 participants and confirmed our assumptions that FRM integration will improve the usability of BI tools and increase the benefits that can be gained from data resources. It also highlighted the potential benefits of collecting value-driven usage metadata and using it to generated usage recommendations
Original languageEnglish GB
Title of host publicationMediterranean Conference on Information Systems (MCIS) 2010 Proceedings
StatePublished - 2010


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