Data Governance: A Challenge for Merged and Collaborating Institutions in Developing Countries

Organisations now invest in ICT solutions to drive business activities and to provide the agility sought within changing environments. Owing to many reasons including inadequate financial resources, organisations in developing countries are characterised by mergers of two or more institutions. It means therefore that disparate systems with different data management schemes are merged or made to collaborate making access to quality data almost impossible. In turn, a level of inefficiency finds its way with potential to generate inaccurate, missing, misinterpreted and poorly defined information. This research is motivated by the need to investigate data governance challenges in institutions within developing countries that are characterised by complex dynamics rooted in merged and collaborating environments. The study has been empirically scoped to explore data governance challenges in a large university of technology in the Western Cape Region of South Africa as a developing country. The challenges with regards to ICT and data governance are equally applicable in higher education institutions as they do in business organisations. Higher education institutions have a growing ICT infrastructure used in everyday activities and online functionality, making them prone to data problems. Challenges related to data management in universities are a lot more pronounced in universities which were established through the merging of independent institutions and also those that exchange data through collaborations. Thematic analysis has been employed within the theoretical lens of two models, contingency model (Wende and Otto 2007) and the data governance decision domain model (Khatri and Brown 2010). Analysis of data through the two models led to the development of a data governance framework applicable to the case under study and deemed to apply to any organisation in the same context. Challenges related to data principles, data access, data quality, data integration, metadata, data lifecycle, and design parameters emerged as the main findings from the study. Since the institution under study was established through a merger of independent technikons, the findings were deemed to be applicable to many other institutions where mergers and collaborations characterise their environment.