What is it?
A fundamental premise of data governance is that data is governed to meet the needs of the business. An agency’s data governance program should be driven by the strategic priorities of the organisation. For example, if poor data quality is preventing an agency from achieving a key strategic outcome, then the focus of the data governance program would be on improving data quality. If having a single view of the customer (SVOC) is important, then Masterdata management would be prioritised in the data governance program. Of course, agencies may need to focus on more than one issue at once.
Why is it important?
Having a clear business-aligned strategy for your agency’s data governance program will ensure that data governance and management activities support the achievement of desired business outcomes. It will also ensure that the data governance program delivers tangible benefits to the organisation in the short-term. By demonstrating the value of data governance for the organisation, this should allow you to gradually build staff and senior executive buy-in for your data governance initiatives and allow you to scale the program across the organisation.
What good looks like
Business-aligned: the data governance program is tailored to the agency’s business needs and strategic objectives.
Compatible: the data governance program takes into consideration specific organisational constraints and is compatible with the cultural context.
Incremental: the data governance program is implemented incrementally across the organisation and initiatives are prioritised based on risk and value.
Measured: data governance and management initiatives are monitored, analysed and measured to ensure that interventions are achieving desired outcomes.
Collaborative: the data governance program is agreed by key stakeholders across different functions of the organisation and all staff participate in implementing good data governance practices.
Communicated: the vision for the data governance program and its alignment with the agency’s strategic objectives should be communicated to staff at all levels.
How to achieve good practice
Business-aligned: the data governance program is tailored to the agency’s business needs and strategic objectives.
Compatible: the data governance program takes into consideration specific organisational constraints and is compatible with the cultural context.
Incremental: the data governance program is implemented incrementally across the organisation and initiatives are prioritised based on risk and value.
Measured: data governance and management initiatives are monitored, analysed and measured to ensure that interventions are achieving desired outcomes.
Collaborative: the data governance program is agreed by key stakeholders across different functions of the organisation and all staff participate in implementing good data governance practices.
Communicated: the vision for the data governance program and its alignment with
What problem are you trying to solve?
What outcomes do you want to achieve?
How will data work to meet your agency’s needs?
What kinds of data does your agency need access to?
How are you going to track, assess and monitor progress?
- Analyse the current state by undertaking a Data Governance & Management (DG&M) Capability. Once a business problem has been identified, it is useful to undertake a Data Governance & Management (DG&M) Capability to understand the context in which the problem is occurring and identify focus areas for your data governance program.
- Identify focus areas for your data governance program. This should be done by working with stakeholders across all functions of the organisation to determine what data governance activities will have the greatest impact on the business.
Plan your data governance response. Once the focus areas have been selected, decide what data governance mechanisms – such as policies, procedures, processes, standards, structures – will be implemented to ensure the resolution of the problem.
Develop metrics to assess whether the data governance response is helping to solve the problem. Start small and set SMART goals (specific, measurable, attainable, result-oriented, time-bound) with clear metrics to assess whether the response is achieving desired outcomes.
Communicate the success of data governance interventions to staff to ensure that they understand how the data governance program aligns with the agency’s strategic objectives.
Repeat the process. As with all large and complex projects, the key to success is to start small, address a well-defined problem, communicate the outcomes of the intervention to staff, and repeat the process and allow the program to scale gradually.
Questions to ask yourself
How are data-related decisions made within your organisation? |
What data assets will your data governance framework apply to? (consider the scope of the information which the data falls into rather than the actual dataset) |
Who are you developing this data governance for? Who are the key stakeholders involved in data management, and what are their roles and responsibilities? |
What types of data does the organisation collect, process, and store? How is data currently managed and used across different departments and systems? |
What are the existing data governance practices, if any, and how effective are they in meeting the organisation's needs? |
What are the legal and regulatory requirements related to data management and privacy? How is compliance ensured? |
What are the potential risks and vulnerabilities related to data, including security breaches and data leaks? |
How is data quality assessed and maintained? Are there any data quality issues that need to be addressed? |
How is data shared and exchanged with external partners, and what safeguards are in place to protect sensitive information? |
How does the organisation handle data access and permissions? Is there a need for data access controls or data segmentation? |
What are the data retention policies, and how is data disposed of when it is no longer needed? |
How will the organisation handle data governance in the context of emerging technologies like Artificial Intelligence and Internet of Things (IoT)? |
How will the data governance strategy align with the overall organisational culture and values? |
What are the budgetary considerations for implementing and sustaining the data governance strategy? |
How will the organisation ensure ongoing engagement and participation from stakeholders throughout the data governance process? |
How will data governance policies be communicated and enforced across the organisation? |
How will the organisation stay agile and adapt the data governance strategy to evolving needs and technological advancements? |
How will the data governance strategy balance the need for data security and privacy with the organisation's desire to leverage data for innovation and growth? |
Important Information
As organisational and data needs change and data volume and complexity increase, decisions about how to govern data will need to evolve. A formalised enterprise-wide strategy and process for making these policies and decisions will need to be in place and be continuously monitored and updated to drive business improvements.
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Last updated 11 Jul 2024