Data Governance Policies: Setting the standard to transform the control of your dataUnderstand how data is fuelling your business through setting data standards across the organisation, backed by robust polices and incisive conformance rules.

A key component of good data governance – rules and best practices that ensure your data is accurate, consistent, accessible and safe – is a well-defined data governance policy, along with its supporting conformance rules.

Organisations hold, and are responsible for, a vast amount of information which must be kept safe from security breaches. According to ICO’s data security incident report, there were over 8,000 incidents reported in 2023, with the health sector having the most incidents. Although not all of the reported data incidents were cyber (i.e. that had an online or technological element), it shows a need for better data processes and procedures to reduce these incidents.

A well-thought-out data governance policy is the foundation of your data strategy. It defines your approach to data use, desired improvements and future management practices, aligning with your business goals.

Conforming data not only minimises errors and duplicates but also ensures data accuracy, improves data analysis and increases data reliability. It also allows for better data-driven decision-making and seamless integration across different systems.

Another benefit of data consistency is that it plays a key role in regulatory compliance. For example, the General Data Protection Regulation (GDPR) mandates specific data handling practices. Conformance rules aligned with GDPR ensure your organisation meets these legal requirements.

Examples of data conformity

Not only does a data governance framework support your data governance policy and conformity rules, but it also guides your organisation towards its data governance goals. A well-defined framework ensures everyone is on the same page, fostering a data-driven culture and promoting responsible data practices.

Why are data governance policies and conformance rules important?

The benefits of a well-defined data governance policy and strong data conformance are numerous; they include improving data quality and increasing efficiency.

Improved data quality

Consistent data formats and definitions within your data governance policies ensure that data is being stored, collected and used throughout your organisation accurately and consistently. Through the improvement in data quality, the business will improve process outcomes, potentially reducing costs and compliance issues.

Regulatory compliance

Many industries and countries around the world have data privacy regulations like GDPR to protect consumer data. A strong data governance policy helps ensure compliance with these regulations by defining and enforcing key policies and procedures. Not only does data governance reduce the risk of non-compliance, but it also helps maintain trust with customers and stakeholders who can see that their data is being handled correctly.

Increased efficiency

Streamlined data management processes outlined in a data governance policy save time and resources as they ensure everyone within an organisation is using the most up-to-date, accurate data. This allows employees to focus on core business activities, without the need to maintain individual data sources or spend time searching for the most accurate data source.

Enhanced security

Data governance policies establish access controls and security measures to protect sensitive information. These policies should outline who has access to what data, why the access should be granted and how data should be protected when it is being transferred or stored. All of these policies mitigate the risk of data breaches by ensuring sensitive data is well-guarded with access only given to those who need it.

Who needs data governance?

Any organisation that collects, stores or uses data can benefit from a data governance policy. This includes businesses of all sizes, from small start-ups to large enterprises and in any sector, for example:

A key benefit for all of these sectors is an increase in straight-through processing (ie. processes successfully completing without any human intervention). This is a key driver of business performance as it can reduce headcount and cost significantly.

How to develop a data governance policy

Here are some initial steps to establish a data governance programme:

Define goals and objectives

Start by outlining and putting together a list of your data governance goals. Do you want to improve data quality for better decision-making? Or perhaps the goal is to enhance data security to minimise breaches or ensure regulatory compliance with GDPR or other relevant laws. Clearly defined goals and relevant objectives to achieving those goals, will guide your policy development and ensure it aligns with your overall business objectives.

Identify stakeholders

Data governance is a collaborative effort. Identify key stakeholders across various departments who will be impacted by the policy. This may include IT, legal, compliance, data analysts and business unit leaders. Involving these stakeholders from the outset fosters buy-in and ensures the policy addresses their specific needs.

Data inventory

Conduct a comprehensive data inventory to understand the types of data your organisation collects, stores and utilises. This includes identifying data sources, formats and locations. Having a clear picture of your data landscape serves as the foundation for establishing data ownership, access controls and data quality standards.

Define data standards and processes

Define clear data standards that ensure consistency and accuracy across your organisation. This may involve standardising data formats, naming conventions and data entry procedures. Additionally, establish data lifecycle management processes that outline how data should be created, stored, accessed, archived and ultimately disposed of.

Implement a data governance framework

A data governance framework provides the structure for implementing and maintaining your data governance policy. It defines roles and responsibilities for data stewards, data owners and data users that cover data ownership, access control and data quality management. Additionally, it establishes processes for data monitoring, auditing and reporting. This framework ensures accountability and ongoing adherence to the data governance policy.

Develop and implement data governance policy

With a clear understanding of your goals, stakeholders and data landscape, you can develop a formal data governance policy document. This document should outline the principles and procedures for data management, addressing aspects like data security, access controls, data quality and compliance. Once finalised, share the policy across the organisation, ensuring everyone understands their roles and responsibilities and buys into the new policy.

Communicate and train

Effective communication and training are essential for successful data governance. Regularly communicate updates and changes to the data governance policy so all stakeholders are aware. Look at implementing training programmes to educate employees on data security best practices, data quality procedures and their specific roles within the data governance framework. An informed and engaged workforce is crucial for ensuring the effectiveness of your data governance policy.

Monitor and enforce

Data governance is an ongoing process. Regularly monitor adherence to the data governance policy through data quality checks, access control audits and user activity logs. Address any identified gaps or non-compliance issues promptly. Enforce the policy through disciplinary actions or system limitations as necessary, though this should be a last resort unless major issues occur. Regular reviews of the data governance policy ensure it remains relevant and effective in today’s ever-changing data landscape.