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Traditional data governance

This page describes traditional data governance, when it is useful, and what it involves. It also highlights some of the limitations of a traditional approach to data governance.

What is traditional data governance?

Data governance is the series of decision-making rights over what you can do with data, and when.

Good governance helps to establish and communicate the norms associated with data in a way that all users of the data can understand. This means everyone using data in an organisation can operate in an agreed and consistent manner.

Traditional data governance normally employs a top-down approach to data-related decision-making and policy development. It relies on a governing body to set the rules, provide decisions and support conflict resolution related to data use.

Governing bodies are typically made up of senior leaders. Through various mechanisms, operational staff are provided with outcomes from the governing body and are responsible for applying them appropriately to their work.

A traditional data governance approach commonly operates with a risk-based view of data.

An organisation using this style of data governance will often prioritise its rules and processes for managing risks associated with the data for which it has responsibility. This approach is meant to eliminate or minimise any detrimental results that arise from the mishandling of that data.

What does a traditional approach to data governance involve?

A traditional data governance model revolves around the use of governing bodies, responsible for setting the direction and rules for what it deems acceptable use of data in an organisation.

These bodies can also provide additional guidance such as establishing and approving data standards for the organisation. As there is a need for a significant level of experience and a strategic perspective to carry out these responsibilities, governing bodies are normally made up of an organisation’s most senior leadership.

Operational staff are the recipients of the rules and standards set by the governing body. These staff are responsible for understanding the data-related rules and standards in the context of their day-to-day jobs and applying them appropriately within their work environments. In this way high-level concepts associated with good data practice, and reflecting organisational norms, become a part of day-to-day operations.

To help manage compliance and promote good data practice, the governing body can delegate some of their powers to data stewards or data custodians. These stewards or custodians have specific responsibilities for making sure operational staff follow the rules and standards for agreed data use and can also provide advice as data subject matter experts.

The positioning of these roles within the organisation’s hierarchy will vary, depending on the organisation’s level of data maturity, its data culture, its structure, and the specific responsibilities required.

It is advantageous for your data stewards or custodians to have an understanding of the operational perspective associated with the area of the organisation within which they are positioned.

Why take a traditional approach to data governance?

A traditional approach offers several advantages to delivering successful data governance.

Firstly, it is a familiar model that typically aligns well with the existing hierarchical structure of most organisations. The required delegation of responsibilities is generally straightforward, since it can often leverage existing delegation structures.

When an organisation reflects low data maturity and there is no formalised approach to data governance in place, a traditional approach is conceptually simple to establish alongside existing organisational policies and governance arrangements.

Replacing ad-hoc processes with a clear set of defined data roles and responsibilities, along with a familiar mechanism for distributing governing body decisions amongst staff, improves an organisation’s ability to realise value from the data it uses.

In this regard, a traditional data governance approach often doesn’t require major investment to establish what is needed for most organisations that handle data.

What are the limitations of a traditional data governance approach?

While a traditional data governance approach can help define roles, create standards, and assign accountability within an organisation, and is particularly useful where there is no defined data governance practice already in place, there are limitations with the approach.

By its nature, traditional data governance can perpetuate an overtly data-centric approach, rather than one that incorporates business or data user needs as drivers. This can result in a level of inflexible data practice, which creates barriers to effective data use in environments that are dynamic and reflect rapidly changing user needs and demands.

The top-down hierarchy used in a traditional approach to data governance does not readily allow the perspective of operational staff to travel upwards, and influence policy and decisions on data practice.

This can lead to workers at the coal face working under rules and standards that they don’t agree with, don’t feel align with or acknowledge their needs, and in their view don’t reflect reality. This in turn can lead to staff dis-engagement and an undermining of the overall data governance approach.

Traditional data governance can in some instances create needless burden on those working with the data, especially if policies aren’t reviewed on a regular basis. Under a traditional data governance model, policies that are no longer fit for purpose may hinder productivity until the governing body reviews or refreshes them. It can also leave those working with the data feeling left out of the policy-making process.

To empower operational staff to share their perspectives, and to make sure organisational data strategy is relevant at the operational level, a holistic data governance approach is useful.

Holistic data governance is designed to acknowledge and leverage the experience and perspective of staff at all levels, from operational to senior leadership, while ensuring those different perspectives also work in a cohesive and mutually supportive manner.

Staff in this scenario remain engaged, are therefore more likely to be accountable and add value to overall data governance and practice, meaning the organisation is more likely to maximise the value of its data.

Holistic data governance


The resources in this section provide an overview of how a traditional approach to data governance can function. They represent government examples but can be applied to any organisation.

Toitū te Whenua, Land Information New Zealand - Steward and Custodian Framework

Please note that this framework is historic. It is not part of any current work programme at Toitū te Whenua Land Information New Zealand, and is not in use. Some of the general data management content has been superseded by more recent data management principles and guidelines.

Te Tari Taiwhenua, Department of Internal Affairs – Data and Information Management Roles and Responsibilities

This work represents an historic example of traditional data governance and has been largely superseded by the Data and Information Governance Toolkit Guidelines, it is intended to be a reference document only.

Data and Information Governance Toolkit Guidelines

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Content last reviewed 7 September 2022.