Data Governance has received much attention in both the academic and practitioner communities over the past 15 years. Compared to the even more recent concept of Data Governance, IT governance has evolved from the initial concept of corporate governance. In the past year, the interest has increased with the evolution of the modern data stack and cloud adoption, along with improved Data Literacy around the globe. There has been more and more research to determine the ideal Data Governance model, or framework, for an organization. However, it has been debated whether there might not be one model that perfectly fits the needs of every business.
Similar to organizational management and IT governance, Data Governance functions are critiqued for their assumptions of relation with fit and performance, along with rational actors, and design parameters like organization structure. As organizations formalize Data Strategy, and governance functions assess, direct, and monitor the implementation of data objectives, there can be more standard approaches to Data Governance.
What Is the Core Focus of Governance in an Organization?
It was the Hawley Committee report in 1994 that first identified data as an asset, defining it as “data that is or should be documented and that has value or potential value.” Data Governance focuses on the decision rights related to the data assets and the network of relations to ensure the quality, consistency, usability, security, privacy, and availability of the data. This can be achieved through standardized as well as formalized processes, roles, and associated responsibilities and required technology to implement this direction required to govern data.
Is Data Management Different from Governance?
It is critical to distinguish the term “governance” from the term “management” in the context of Data Governance. It should be noted that the principal difference between “governance” and “management” is that governance refers to the decisions that must be made and who must make them. This is to ensure effective resource allocation and management of data operations. On the other hand, Data Management involves implementing those decisions that arise from assessing and monitoring either existing controls or the environment that includes advancements in technology and the market. The activities required for Data Governance can, therefore, be distinguished from those needed for Data Management since management is influenced by governance. Data Governance is oversight of Data Management activities to ensure that policy and ownership of data are enforced in the organization. The emphasis is on formalizing the Data Management function and associated data ownership roles and responsibilities. In addition, governance also ensures that Data Management as a service is sustainable as a function, thereby enabling active management of data.
How Does Corporate Governance Influence Data Governance?
Let’s get back to the basics of the evolution of corporate governance that will give a perspective to Data Governance. In the economic debate concerning the impact of corporate governance on performance, there are basically two different models of the corporation: the shareholder model and the stakeholder model. In its simplest sense, the shareholder model of corporate governance refers to senior management’s formal accountability to shareholders. Meanwhile, the stakeholder model of corporate governance describes the network of formal and informal relationships involving the company. The stakeholder approach stresses how stakeholders can contribute to a firm’s long-term success and shareholder value, but also recognizes that business ethics and stakeholder relations can impact a firm’s reputation and long-term success.
Data ownership has always been perceived to be the core tenet of the Data Governance model that helps drive decisions with accuracy. Recently, we have been seeing variations in the data ownership models including the information technology, business divisions, and data office, federated between business divisions and IT. The stewardship model can also be perceived to be another tenet of Data Governance that’s an evolution to the data ownership model. While data ownership can be more formalized, steward identification can be an alternate approach to imparting accountability across the organization that can impact the long-term value of data. Certain distinctive features of a good Data Governance model aligned with corporate governance are specifically:
To conclude, with each passing year, data is becoming more visible on corporate agendas, increasing shareholder expectations about creating or protecting customer interests. During the big data era, data has become an important strategic resource for organizations. Every aspect of social, economic, and citizen interaction with government and corporations has been transformed by data in the last decade. A growing number of citizens are demanding increased accountability from their governments, health care systems, and non-profits. Also, to make better investment decisions, shareholders expect corporations to disclose accurate information. By aligning Data Governance principles and framework with corporate governance, organizations can manifest their business objectives with practical measures.