The need of Data Governance
IT governance is a segment within organizational management focused specifically on the IT function. Hence, IT governance is responsible for the administration and execution of the IT strategy, the underlying IT projects and the operations of all IT systems. IT governance methodology differs from one organisation to another depending on the traits and requirements of the company (Borja et al., 2018). Nowadays, IT constitutes a large footprint, in terms of costs and strategic decision, in almost every industry. Hence, IT governance is responsible for any decisional and strategic rights, as well as the accountability responsibilities associated to such decisional rights (Gregory et al., 2018). An effective IT governance strategy within the organization, positively influences the innovation of products and processes (Borja, et al., 2018). The traditional IT governance model is based on steering and control, whereas steering provides direction and control is related to the adhesion of abiding to rules (Ajis & Baharin, 2019). Data is a key driver of IT and as such the need to have an appropriate governing body specifically for the data domain is deemed necessary.
Distinguishing Data Governance from IT Governance
The processes, components and relationship amongst IT and data governance models are depicted in the below image. IT and data governance functions have common purpose in the sense of ownership and accountability, whilst focusing on standardisation and documentation. In IT governance, different committees and frameworks direct the strategy and control the established rules, whereas Data governance is focused on the data domain entirely using the processes agreed in the IT governance.
IT and Data governance
The objectives of Data Governance
Data governance is a subset of the IT governance body specifically responsible for the data within the organization. Through appropriate and defined procedures, this governing body is responsible for the management of the availability, usability, integrity, and security of the data, thus guaranteeing data quality management within the organization (Wende, 2007). The data governance body is responsible for data quality and access through all the relevant phases, i.e. decisional, implementation, operational and support phases, with the support of top top-level management. The International guide to data management body of knowledge (DMOK) proposes a data management organisation. In practical terms, this kind of organization is only possible in large set-ups. Medium and small companies (SMEs) need to adapt such models according to the available resources and requirements, however such a structure provides a clear understanding of competencies of steering and control for data governance.
Evaluating Data Governance adoption within the organisation
Data governance adoption within the organisation can be measured using qualitative and quantitative metrics as proposed by the Stanford data governance capability maturity model (Saputra et al., 2018). Such exercise would be useful to determine any pitfalls and identify if new resources are needed to further grow within the data governance practice.
As organisations are leveraging data to achieve competitive advantage, the executive team needs to ensure that the data strategy is aligned with overall corporate strategy. Furthermore, with the ever increasing regularisation of data (e.g. GDPR), organisations need to ensure that their data is secure. Due to the above requirements, organisations need to embark on a transformational journey to put data management at the centre of the IT and corporate strategy.
Ajis, A. F. M., & Baharin, S. H. (2019). Dark Data Management as frontier of Information Governance. 2019 IEEE 9th Symposium on Computer Applications & Industrial Electronics (ISCAIE). https://doi.org/10.1109/iscaie.2019.8743915
Borja, S., Kim, K., Yoon, H., & Hwang, J. (2018). IT Governance Effectiveness and Its Influence on Innovation Product and Process. 2018 Portland International Conference on Management of Engineering and Technology (PICMET). https://doi.org/10.23919/picmet.2018.8481752
Gregory, R. W., Kaganer, E., Henfridsson, O., & Ruch, T. J. (2018). IT Consumerization and the Transformation of It Governance. MIS Quarterly, 42(4), 1225.
Saputra, D. A., Handika, D., & Ruldeviyani, Y. (2018). Data Governance Maturity Model (DGM2) Assessment in Organization Transformation of Digital Telecommunication Company: Case Study of PT Telekomunikasi Indonesia. 2018 International Conference on Advanced Computer Science and Information Systems (ICACSIS). https://doi.org/10.1109/icacsis.2018.8618255
Wende, K. (2007). A model for data governance-Organising accountabilities for data quality management. ACIS 2007 Proceedings, 80.