2017Diva portal (Dalarna University Library)Open access

Research proposal: Facilitating the Implementation of Self‐Service Business Intelligence

Christian Lennerholt

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Abstract

Business Intelligence (BI) is widely implemented and used by many organisations. In a traditional BI system, power users serve less experienced casual users. Power users analyse and gather data requested by casual users, and produce reports and visualisations that casual users base their decisions on. When data volumes and the usage frequency of a traditional BI system increase, power users have problems serving all the requests from casual users. The Self Service Business Intelligence (SSBI) approach can enable users to be more self-reliant and less dependent on power users. Although SSBI promises more benefits compared to a traditional BI system, many organisations fail to implement SSBI. This research proposal aims to facilitate the implementation of SSBI by suggesting recommendations for how to manage associated challenges when implementing SSBI. The proposed research method is a longitudinal study using multiple case studies. The expected results will describe how to implement SSBI on a desired maturity level while managing the associated challenges. The results consist of a framework that lists known associated challenges when implementing SSBI and a maturity model for SSBI, which defines the levels and characteristics needed for developing SSBI implementation. An expected contribution of this research is an increased adoption rate of SSBI.

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What this paper is about

Business Intelligence (BI) is widely implemented and used by many organisations. In a traditional BI system, power users serve less experienced casual users. Power users analyse and gather data requested by casual users, and produce reports and visualisations that casual users base their decisions on. When data volumes and the usage frequency of a traditional BI system increase, power users have problems serving all the requests from casual users. The Self Service Business Intelligence (SSBI) approach can enable users to be more self-reliant and less dependent on power users. Although SSBI promises more benefits compared to a traditional BI system, many organisations fail to implement SSBI. This research proposal aims to facilitate the implementation of SSBI by suggesting recommendations for how to manage associated challenges when implementing SSBI. The proposed research method is a longitudinal study using multiple case studies. The expected results will describe how to implement SSBI on a desired maturity level while managing the associated challenges. The results consist of a framework that lists known associated challenges when implementing SSBI and a maturity model for SSBI, which defines the levels and characteristics needed for developing SSBI implementation. An expected contribution of this research is an increased adoption rate of SSBI.

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Available abstract

Business Intelligence (BI) is widely implemented and used by many organisations. In a traditional BI system, power users serve less experienced casual users. Power users analyse and gather data requested by casual users, and produce reports and visualisations that casual users base their decisions on. When data volumes and the usage frequency of a traditional BI system increase, power users have problems serving all the requests from casual users. The Self Service Business Intelligence (SSBI) approach can enable users to be more self-reliant and less dependent on power users. Although SSBI promises more benefits compared to a traditional BI system, many organisations fail to implement SSBI. This research proposal aims to facilitate the implementation of SSBI by suggesting recommendations for how to manage associated challenges when implementing SSBI. The proposed research method is a longitudinal study using multiple case studies. The expected results will describe how to implement SSBI on a desired maturity level while managing the associated challenges. The results consist of a framework that lists known associated challenges when implementing SSBI and a maturity model for SSBI, which defines the levels and characteristics needed for developing SSBI implementation. An expected contribution of this research is an increased adoption rate of SSBI.

Key concepts: Service (business), Business intelligence, Computer science, Knowledge management, Business, Process management, Data science, Marketing

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