In 3 steps towards effective data governance
Practical guide for organisations who want to get a grip on their data
- Article
- Data Engineering
- Data governance
In this two-part article series, we explore the importance of data governance and offer a practical guide for implementation within your organisation. In the first article, we explained why you can’t afford to delay. Now, we break down how to get started, step by step.
This article series consists of 2 articles:
- Why you can't afford to wait on data governance any longer
- (Current article) In 3 steps towards effective data governance
Step 1: Align on the why
Start by lighting the spark: speak with your colleagues and stakeholders and convince them that your organisation needs to proactively manage its data.
Illustrate how poorly managed data and low data quality hinder the execution of corporate strategy and prevent real progress. Show how data governance enables better decision-making, boosts efficiency, supports compliance, and mitigates risk.
And as always, be context-specific: share internal examples that resonate with your audience.
Step 2: Define roles & responsibilities
The next step is to assign data governance roles to allocate responsibilities. Because as we all unfortunately know, if no one feels ownership, problems don’t get solved. It’s simply human nature.
Begin by identifying data owners and data stewards. A data owner should be a senior business-side leader, someone with authority, budget, and accountability for a data set. They are supported by data stewards in day-to-day tasks.
All data owners report to the Data Governance Council, chaired by a C-level executive above them. This ensures that decisions, progress and escalations are properly safeguarded.
Finally, map out your data producers and consumers. Only when producers understand consumer needs can they deliver quality data.
Step 3: Build the framework and start small
When all the main stakeholders are on board and roles and responsibilities are clearly defined, it's time to get the fire burning. Here you want to focus on three key areas:
- Corporate strategy: Articulate why data governance is essential for your organisation to achieve its strategic goals. This forms a key part in securing that crucial management buy-in. The senior leadership needs to know: “You can’t trust the numbers without governance”. The good news? You had already thought this through under step 1. 😉
- Data governance framework: Work out the main data governance policies and processes: what needs to be done, and how it will be carried out. Start with the most critical documentation and expand from there. Consider using simple visuals in addition to detailed diagrams and text heavy documents. Involve stakeholders in shaping the framework and secure a formal mandate from the data governance Council.
- Implementation: Roll out the data governance framework in phases to give people time to adapt. Start small and gradually expand by starting with high impact use cases, such as operational excellence, master data management, a new data warehouse or upcoming data migration. A phased approach helps build momentum and allows early learnings to inform the broader rollout.
Pro tip: don’t start with a tool! Use basic documentation first. Buy-in from business users is easier when processes come before technology.
Key takeaways
- Bad data costs more than data governance. Without a structured approach, teams keep fixing the same problems and risks will accumulate.
- Governance isn’t about tools, it’s about people, processes, and breaking silos. The right people must make the right decisions.
- Start small and show early wins. Trust builds with results. A visible success story can go a long way in sustaining momentum.
This is an article by Guus van Loon
Guus is a data strategy consultant at Digital Power. He helps organisations turn data into long-term business value by aligning data strategy, change management, and decision-making with company goals. His background in cognitive neuroscience gives him a profound understanding of human behavior, enabling him to bridge the gap between tech specialists and business stakeholders.
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