Most organisations rely on their data as a strategic asset to thrive and operate efficiently in the most competitive business landscape. Maintaining a smoothly running operation backed with data requires careful consideration of data ownership, a crucial but often neglected aspect.
While data ownership might appear to be a simple concept, implementing it can pose challenges. Assuming the role of a data owner entails significant responsibility, which can make suitable candidates shy away from taking on the role.
Lack of data ownership also means different business functions still adopt their own strategy leading to data silos. It becomes easy for data to be less accurate, affecting the ability to make performance-related decisions. To manage your operations efficiently, you need detailed insight and good data quality, which can be enhanced by data ownership.
What is Data Ownership?
Data ownership is an essential principle of data governance that explains ownership of enterprise-wide data. Think of data as a property owned by a landlord. A landlord has the responsibility to ensure that the property is managed properly. They also have the right to assign access privileges to other people.
With data ownership, an organisation can specify individuals known as data owners to manage certain aspects of data. Data owners can remediate issues arising from data or delegate them to data stewards who work with them on a day-to-day basis. Data ownership revolves around accountability and responsibility. Just like landlords, data owners make the ultimate decisions by ensuring the accuracy and quality of the datasets within their domains.
Why does data ownership matter?
Implementing data ownership prevents unnecessary ambiguity that may arise when trying to figure out persons with knowledge of a specific dataset. One of the most common problems with the lack of data ownership is that business units operate in data silos and make their own decisions. An ownership structure is necessary to maximise the value of data across the organisation.
Data ownership establishes accountability. A data owner is seen as an individual responsible for all decisions made around specific datasets. Having a data owner ensures that there are defined controls for access to data. A data owner will also determine quality dimensions and remediate data issues in a manner that is consistent across the organisation.
The concept is also essential to data governance strategy. At the heart of every data governance framework is intentional ownership. A data owner plays a key role in aligning strategic business goals with overall data governance. They make trustworthy data driven decisions which will drive a data-centric culture within the organisation.
Data ownership facilitates collaboration as data owners can decide who they want to share their data with and under what conditions. A data owner also works closely with data stewards and data custodians to ensure the proper management of datasets within their domains. This can promote data sharing for collaborative and innovative purposes.
How do you choose the right data owner?
You might understand the importance of data ownership but struggle to implement it while starting out your data governance journey. Having multiple business functions with different objectives makes it hard to identify the right person to manage data appropriately. The first step in determining data ownership is to involve business users and relevant stakeholders to figure out the right person who owns the data within the organisation. This can be done by evaluating the different business functions within your organisation and understanding how they work with diverse sets of data.
The next step will be to identify individuals suited to take on the role of data owners and establish responsibilities. A simple way to figure this out is to look for individuals accountable for the data quality within an organisation. It is important to have as a data owner a strategic stakeholder who has access to resources to carry out audits or other activities required to ensure the quality of the data. Once the data owners have been identified, their roles and responsibilities will be mapped out to provide a comprehensive chart of who is responsible, accountable, consulted and informed on datasets.
There is no ‘one size fits all’ model for data ownership. It is therefore important to consider other factors at play such as culture, capabilities, and behaviours within an organisation to have a sustainable data ownership model. The right individuals must also be in place to deliver the objectives of the data governance strategy set out within your organisation.
At Oakland, we understand that data ownership is an essential step in developing a data governance framework. Our proven ownership model designed to suit your organisation’s needs focuses on responsibilities and accountabilities that support a value creating data culture. We support your data management trip by identifying the best operating model that articulates roles, responsibilities, and decision-making processes within your organization. We also create accountability by ensuring the right functions within your organisation are represented. If you are looking for help with your Data Governance challenges please reach out for an assessment to kickstart your data governance journey.
Yejide Adewakun is a data governance consultant at The Oakland Group.
