Original Research

A Data Governance Maturity Evaluation Model for government departments of the Eastern Cape province, South Africa

Olutoyin Olaitan, Marlien Herselman, Ntombovuyo Wayi
SA Journal of Information Management | Vol 21, No 1 | a996 | DOI: https://doi.org/10.4102/sajim.v21i1.996 | © 2019 Olutoyin Olaitan, Marlien Herselman, Ntombovuyo Wayi | This work is licensed under CC Attribution 4.0
Submitted: 04 May 2018 | Published: 24 July 2019

About the author(s)

Olutoyin Olaitan, Department of Information Systems, University of Fort Hare, Alice, South Africa
Marlien Herselman, Meraka Institute, Centre for Scientific and Industrial Research, Pretoria, South Africa
Ntombovuyo Wayi, Faculty of Management and Commerce, University of Fort Hare, Alice, South Africa


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Abstract

Background: There are different uses of data in an organisation. Data are required for reporting purposes, decision-making and providing access to vital facts to enable work processes across business units. Data are central to an organisation’s capacity in anchoring fiscal and strategic plans on valid, accurate and current facts, and are also a vital element in an organisation’s capacity to meet legal, compliance and risk management requirements. To ensure sound decision-making, data must be treated as an asset within organisations, with sound data governance principles entrenched and employed for data handling from inception to deletion.

Objectives: This article proposes a Data Governance Maturity Evaluation Model for government departments of the Eastern Cape province, South Africa.

Method: The methodology for this study is Design Science. The Design Science Process Model, was followed in the development, design and demonstration, and evaluation and communication of the data governance framework. A sequential exploratory mixed-method approach was used for data collection and analysis.

Results: A conceptual data governance maturity model was proposed for government departments of the Eastern Cape province, South Africa. The model was tested through an exploratory sequential mixed-method approach of data collection and analysis. Data were collected from four departments.

Conclusion: The results of the survey confirm the applicability of the model in the set context and reinforced the findings from the literature that maturity models can be used to improve or enhance data governance in public enterprises.


Keywords

Data governance; maturity models; Data Governance Maturity Evaluation Model; data integrity; government departments.

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