Data Governance, The One to Rule Them All

Data driven company…

We hear these three words more and more often. Recent research by IDC [1], sponsored by Tableau, has showed that 83% of CEOs want their organisations to be more data driven. Why? There are a number of benefits of having strong data culture, such as greater competitive differentiation, increased profits and revenues, higher customer and employee satisfaction. Perhaps, even your company has decided to launch a company-wide strategic initiative, like ‘building a data culture’, in order to fully realise the value of the company’s data assets.

However, becoming a ‘data driven’ business is not an easy task, particularly for mainstream legacy companies. According to the IDC’s survey, only 16% of organisations in the UK are data leading.

Companies face many challenges when they embark on the journey to become a data-centric business. In my opinion, the biggest challenge for many companies is the requirement of a holistic approach, which considers all elements of Data Management rather than focuses on a couple of data management elements (Figure 1). Nowadays, to satisfy data-related regulatory compliance requirements companies usually have a number of data management policies and standards, for example, related to data security and data access. However, companies often underestimate the importance of Data Governance, which in the DAMA DMBOK2 framework is recognised as the central element in Data Management because it guides all other data management functions. Moreover, it is often wrongly viewed as just an IT function, not a business function.

Figure 1. The DAMA-DMBOK2 Data Management Framework (The DAMA Wheel).

Data Governance is the exercise of authority and control (planning, monitoring, and enforcement) over the management of data assets. The purpose of Data Governance is to ensure that data is managed properly, according to policies and best practices. Data Governance focuses on how decisions are made about data and how people and processes are expected to behave in relation to data.


Where to start? The first step towards a data driven business is the recognition of the importance of Data Governance by company’s senior leadership team. The Data Governance programme should have a senior leadership owner to ensure that the programme

  • has a strong sponsorship, so that appropriate resources are allocated;
  • is aligned with the business strategy and goals;
  • is focused on prioritised business driver(s).

If your company is just starting its journey, the best approach to introducing Data Governance would be Seiner’s Non-Invasive Data Governance™ approach [1]. It “builds a Data Governance program based on existing roles and responsibilities” rather than by forcing employees to accept Data Governance tasks and responsibilities.

There are also four key roles (and responsibilities) that need to be defined and filled to increase chances of a successful implementation of Data Governance programme at your company (Figure 2):

  • Data Governance Committee – senior leadership team, which consists of Data Owners and business decision makers. It defines the Data Governance strategy, focus areas, metrics/success measures, policies and allocates funding. The Committee also appoints a project team to interview stakeholders, assess company’s current data management state, reviews data architecture and make recommendations with regard to policies, standards and appointment of Data Stewards (for example, following an approach similar to the implementation of the IBM Data Governance Framework [2]).
  • Data Owners (business Data Stewards), who are accountable for data assets (and its quality) within their domain.
  • Data Stewards, who are responsible for day-to-day management of data. They are subject matter experts appointed by Data Owners. They define and control data (while taking stakeholders’ interests into account), and work with other data stewards to resolve any data issues.
  • Technical Data Stewards, who are IT professionals specialising in a particular technical area (e.g. database administrators, data integration specialists).

Figure 2. Stages of a Project on Data Governance Implementation

It is highly likely that the implementation of Data Governance will also require a cultural shift in the way the company operates and thinks about data. Therefore, there will be a need to run in parallel a change management programme, which supports the required organisational cultural change:

  • It should be based on the results of the assessment of data management maturity, capacity to change, collaborative readiness and business alignment.
  • It must include extensive communication and training plans. In particular, the company can adopt one of the DG maturity models [3] and use it to communicate the implementation roadmap from AS IS to SHOULD BE.

What to take home…

Since each company is unique, the approach to its transformation into a data driven business needs to be tailored accordingly. However, there are three key considerations that will help any company with the evolution:

  • Systems thinking approach should be at the heart of the transformation;
  • Data Governance framework should be considered and established at the beginning of the transformation;
  • A change management programme should be used to drive the organisational cultural change.


[1] Dennis, A.L., (2018) ‘Starting a Data Governance Program: What Does it Take?’, Dataversity, 14 March [Blog]. Available at

[2] NASCIO (2009b) Data Governance Part III: Frameworks. Structure for Organizing Complexity, Lexington, KY, NASCIO [Online]. Available at

[3] NASCIO (2009a) Data Governance Part II: Maturity Models. A Path to Progress, Lexington, KY, NASCIO [Online]. Available at

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