Original Research

Inhibitors of business intelligence use by managers in public institutions in a developing country: The case of a South African municipality

Ingrid J. Mansell, Ephias Ruhode
South African Journal of Information Management | Vol 21, No 1 | a1004 | DOI: https://doi.org/10.4102/sajim.v21i1.1004 | © 2019 Ingrid J. Mansell, Ephias Ruhode | This work is licensed under CC Attribution 4.0
Submitted: 16 May 2018 | Published: 26 August 2019

About the author(s)

Ingrid J. Mansell, Department of Information Technology, Cape Peninsula University of Technology, Cape Town, South Africa
Ephias Ruhode, Department of Information Technology, Cape Peninsula University of Technology, Cape Town, South Africa

Abstract

Background: Business intelligence tools play an important role for businesses across all industries for their data and information management solutions. By harnessing the capabilities of business intelligence, companies are able to predict and better meet customer needs. This study investigates factors that inhibit managers’ use of business intelligence tools in a public organisation in South Africa, where there has been evidence of a very low uptake of business intelligence tools.

Objective: The objective of this study was to establish factors that inhibit the use of business intelligence and data analytics tools by managers in public organisations. Organisations are likely to lose their competitive advantage and experience a negative impact on efficiency and service delivery if managers do not make use of analytics in strategic decision-making.

Methods: The study utilised both qualitative and quantitative data. Qualitative data were collected from managers through interviews, whilst questionnaires and daily login recordings were used to collect quantitative data. Quantitative data were analysed using statistical methods, whilst qualitative data were analysed by thematic analysis.

Results: The research revealed a wide range of factors that inhibit the use of business intelligence tools by managers. These factors range from personal, system quality, organisational, macro-environmental, behavioural beliefs and attitudes, effort perceptions and social influence to facilitating conditions.

Conclusion: The article provides a comprehensive contextual situation regarding poor use of business intelligence and analytics tools in a large metropolitan public entity. The findings from the organisation under study would be deemed to apply to similar organisations throughout the country.


Keywords

Business intelligence; data analytics; thematic analysis; South Africa; public institutions; developing countries

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