15 Apr, 2021 / Victoria Gombert Article

3 Elements of a Successful Data Governance Strategy_

Each unique to the organisation, a Data Governance Strategy is the first step to achieve embedded data governance.

A strong foundation for any initiative begins with a strategy. Each unique to the organisation, a Data Governance Strategy is the first step to achieve embedded data governance within any business. This strategy will enable a clear vision of what it is that an organisation wants to achieve and why they want to achieve it, while a data governance framework and process detail the actionable steps an organisation must take to make embedded data governance a reality.

Data is fundamental to almost all business activities, and business activities should be contributing to the overall business strategy. Data Governance Strategy should be aligned with the overall business strategy and help the business achieve its overall objectives through aligning data governance strategy with the business strategy.

By having a structured approach to data governance through producing a clear strategy, data governance will directly help an organisation move towards its overall business strategy – whether that be international growth or increased market share. An organisations Data Governance Strategy should be specific to the particular-business activities and not generic data governance benefits. It is beneficial to have an outcome for business change so it can be communicated clearly and succinctly to the business.

Essential Elements to Successful Data Governance Strategy

When creating a successful data governance strategy, three elements are essential– (1) why, (2) roadmap and (3) end goal. By ensuring these three elements are satisfied in your data governance strategy, the data governance programme will have a strong foundation.

1. Why.

Why is the organisation doing data governance? As mentioned, the Data Governance Strategy must tie back to the organisation-specific benefits and link with the overall business strategy and objectives. Even if the organisation has existing data quality standards in place – a strategy for data governance must be produced with specific benefits as to why data governance will help the business' overall strategy. This will help enable alignment between the data governance strategy and overall business strategy, and help define what the precise benefits the organisation wants to achieve are.

Benefits should be explained in detail. This will give business people a clear understanding of how data governance will help the organisation.

2. End Goal.

End goal is the process of assessing where the organisation wants to aim and land in achieving data governance. In deciding an end goal, the business needs to determine the level of data quality and define the scope of the data governance (for example, it may be unnecessary to govern business emails or word documents). The benefits and costs of differences in data quality and scope should be examined – for example, does the difference between achieving ninety-percent (90%) accuracy or ninety-five-percent (95%) accuracy outweigh the additional costs of increasing the five-percent (5%).

A data governance maturity model can help an organisation assess the current level of maturity to determine an end goal (see below). By first assessing the current level of maturity, it is easier to identify clear objectives and work out what certain data stakeholders need to hear (in terms of specific end goals) to more openly welcome data governance.

The Data Governance Maturity Model shows that through data governance adoption across people, process and technology, an organisation can move from undisciplined to reactive, proactive, and ultimately governed. This model can help an organisation in deciding an end goal.

Dodson, L. (2014, September 29). The celebrity of data: Big data goes big time in your organization.

It may not be necessary to reach the highest level of maturity to meet an organisations objectives, where proactive may be the end goal for one organisation and governed the end goal of another.

It is also important to avoid making the end goal seem too daunting or infeasible. If an organisation sits within the undisciplined area (the lowest level of maturity), then setting the end goal of governed (the highest level of maturity) may seem daunting and unachievable, which may in turn increase resistance to change. In this case, setting a more realistic goal of reactive or proactive will help get the organisation to get started on their data governance journey and enable them to begin caring about their data and achieving more sustainable growth.

3. Roadmap.

Roadmap is essentially the implementation order of the organisations Data Governance Strategy. This is an important part of developing the Data Governance Strategy, as data governance is a long-term change programme – so data governance takes time to embed and therefore long-term business benefits will also take time to be realised. Therefore, by accomplishing ‘quick-wins’, a Data Governance Programme can gain increased support and sponsorship as these quick-wins boost immediate enthusiasm and champion momentum within the business. This may be through implementing the Data Governance Programme to top-level management at first where critical reports are relying on specific data, or another critical area of the organisation. 


This is an excerpt of the e-book Governance of Data in an Organisation by Victoria Calderwood, to be released soon.