You're facing limited resources for data governance initiatives. How do you decide what to prioritize?

Ask the business for help prioritizing. If you have formed a DG council (DGC) with c-suite executives this is best suited for their guidance and direction on priorities. I don’t recommend chasing every request that comes in to the DG team (don’t boil the ocean), escalate the prioritization to the DGC. A tip is to ask the requester(s) to explain the business benefit or impact so that the requests are easier for the DGC to prioritize. If the company has a list of strategic initiatives it’s even better if you can tie requests to one or more of these!

It is important to understand where compromised data is impacting your business. Be it trust, accuracy, consistency, reliability - amongst possible areas of concern - issues that impede efficient and effective operations and decision making processes. As resources and timeline permit, always be bold and think big. But prioritization is about establishing smaller milestones that can be achieved within the known limitations of your team tasked both the way forward to addressing data issues in the organization. Build momentum and more people will jump on board and the participating party will inevitably increase organically, just need to show the stakeholders the way. In small doses. Why small? Daunting is a deterrent and simplicity is king.

In my experience, Not all business units need to implement data governance immediately. Select a few units and implement the data governance for them. This way we can manage the resources well and once DG is successfully implemented to a certain level we can showcase how this practice solved problems for that unit and incorporate more units into the same process based on their needs.

Begin by conducting a thorough assessment of your organization’s data governance needs. Identify the most pressing issues and opportunities for improvement. Consider the current state of data management, the specific challenges faced by different departments, and the potential impact of various initiatives. This initial assessment will provide a foundation for informed decision-making.

It is highly important to understand and measure Analytics maturity within our company, considering that not all departments or organizational areas will necessarily have the same level of maturity. From this initial analysis, we will be able to define a Data Governance strategy that takes into account the different realities, aligned with the expectations, capabilities, and expected results of each area of the company. Evaluating the current situation of the company will allow us to identify the key elements that will enable us to achieve the desired future situation, both at the model level (operational, organizational, etc.) and the roadmap required to achieve it.

Compliance with regulatory requirements should be a top priority. Non-compliance can result in significant legal and financial repercussions. Identify the data governance aspects that are directly tied to regulatory compliance and ensure they are addressed promptly. This not only mitigates risk but also builds a strong foundation for other data governance efforts.

Prioritize initiatives that mitigate the highest risks to your organization. Assess potential data risks, such as data breaches, data loss, and data integrity issues. Focus on implementing controls and safeguards that protect sensitive information and ensure data accuracy. Effective risk management helps safeguard the organization’s reputation and financial health.

Data security is a critical aspect of any corporate Data Governance plan, along with other factors such as accurately knowing the data available, classifying it, and ensuring its accessibility and availability. It is essential to start by establishing clear and concise data policies and standards on how data should be collected, stored, processed, and used within your company. You will also need to establish quality standards to ensure data quality and define how to manage the risks associated with data management. Data policies should be clear and concise so that all members of the organization understand and follow them.

Align data governance initiatives with the organization’s business objectives. Identify which initiatives will drive the most value and support key business goals. This alignment ensures that data governance efforts are not only protecting and managing data but also contributing to the organization’s overall success. Focus on initiatives that enhance decision-making, improve operational efficiency, and support strategic priorities.

The data governance strategy must be aligned with the company's overall strategy and, ultimately, must deliver tangible benefits. In fact, data is not an end in itself: it is primarily a resource that the organization can use to create value and improve its competitiveness. Therefore, to be truly effective and relevant, a data governance policy must be articulated around business needs and processes, with clearly defined objectives.

Engage with key stakeholders to understand their priorities and concerns. Stakeholders, including executives, department heads, and data users, can provide valuable insights into the most critical data governance needs. Their support and buy-in are essential for the success of any initiative. Prioritize projects that have strong stakeholder support and address their most pressing needs.

Before implementing Data Governance, it is important to establish a clear vision of what you want to achieve and the specific goals to be met. This will help to give direction and purpose to data governance in the organization. It is essential to involve all relevant stakeholders in the process to avoid friction within the organization. This includes senior management, IT teams, end users, and other groups that may be affected by data governance policies and processes. Active participation and collaboration from all stakeholders will help to ensure a successful implementation and ongoing commitment.

Adopt a mindset of continuous improvement. Prioritize initiatives that establish a framework for ongoing data governance enhancements. Implement processes and tools that allow for regular monitoring, assessment, and refinement of data governance practices. This approach ensures that data governance evolves with the organization’s changing needs and emerging challenges.

Data Governance should not be seen as a short-term project, but rather as an ongoing process. It is essential to constantly monitor and evaluate the effectiveness of Data Governance policies and processes, and implement improvements as needed. This will ensure that Data Governance remains relevant and effective as needs and regulations change. Implementing, evaluating, reflecting, and improving should be the recurring steps in this wheel of continuous improvement and adaptation.