Step 1: Identify the Data Governance Leadership & Define the Scope
Part of the 10-Step Data Governance Implementation Series
Written for organisations building practical, scalable governance frameworks for responsible data management.
Introduction: Why This Step Matters
Before drafting policies or deploying tools, the first step in implementing data governance is to define who will lead the programme and what exactly will be governed. These two decisions determine how authority flows, how fast the programme will scale, and whether it will gain or lose traction across the organisation.
Governance isn’t about control for control’s sake. It’s about creating clarity and accountability—something that begins with leadership and scope.
1. Defining Governance Leadership
Effective data governance leadership must be strategic, tactical, and operational. Rather than assigning a single leader or generic committee, the leadership structure should include distinct roles aligned with real organisational influence.
Strategic Level – Direction and Sponsorship
- Executive Sponsor: Advocates for the programme at the board or senior management level
- Chief Information Officer (CIO): Aligns data governance with digital strategy and IT infrastructure
- Chief Data Officer (CDO): Leads data vision, risk oversight, and governance strategy
These individuals drive funding, define organisational risk appetite, and elevate governance to strategic importance.
Tactical Level – Policy and Oversight
- Data Governance Council: A cross-functional team of business and technical leaders who review and approve policies, resolve disputes, and prioritise governance work
- Data Governance Lead or Programme Manager: Coordinates the programme’s execution and alignment
- Chief Data Steward: Oversees data stewardship activities, often across domains
This level ensures operational cohesion and cross-departmental coordination.
Operational Level – Execution and Stewardship
- Business Data Stewards: Validate and maintain business definitions, quality rules, and metadata
- Technical Data Stewards / Custodians: Manage system-level enforcement, data lineage, access control
- Data Architects / Analysts: Support modelling, analytics, and documentation
💡 Tip: Always distinguish between ownership (accountability) and stewardship (execution). Confusing the two leads to overloaded teams and unclear expectations.
2. Embedding Governance into Culture
Titles aren’t enough—leadership must be embedded into the organisation’s day-to-day processes. This means:
- Connecting governance to programme boards, transformation projects, and audit functions
- Engaging business owners and data producers early
- Using a RACI matrix (Responsible, Accountable, Consulted, Informed) to define who does what
A RACI matrix ensures governance is not theoretical—it’s visible in how decisions are made.
3. Scoping Governance the Right Way
Governance scope defines what data, departments, or systems are included—initially. Scoping everything at once is a mistake. Instead, choose a focused scope based on business value or risk.
Common Scoping Methods
- Use Case-Driven: Focus on data related to a priority like ESG reporting, customer onboarding, or compliance
- Risk-Based: Prioritise domains with the highest regulatory, financial, or reputational exposure
- Maturity-Based: Start where there’s already a foundation—e.g., teams using data dictionaries or standards
You can also scope:
- Vertically: One department or domain (e.g. HR, finance)
- Horizontally: One governance function across all domains (e.g. metadata or access control)
4. Governance Scope Statement Template
A useful template to align everyone from day one:
Governance Scope Statement – v1.0
Data Domains: HR, Finance, Customer
Systems: ERP, CRM
Departments: ICT, Finance, Marketing
Use Cases: GDPR compliance, operational reporting
Exclusions: Unstructured data, legacy systems (Phase 2)
Review Cycle: Every 6 months
5. Pitfalls to Avoid
- Assigning titles without decision-making power
- Launching with a scope too large to manage
- Ignoring frontline data creators and modifiers
- Skipping documentation of roles and responsibilities
6. What Good Looks Like
- Named leaders across strategic, tactical, and operational roles
- A visible executive sponsor with budget and authority
- A scoped and realistic governance focus tied to actual business priorities
- Documentation and early engagement with affected teams
Summary
Step 1 builds your foundation. It’s where clarity, alignment, and credibility begin. By identifying leadership and scoping governance with care, you prepare the organisation to take meaningful, measurable next steps.
Coming Next
Step 2: Develop a Data Governance Charter
We’ll cover how to write a clear, actionable mandate for your governance programme—aligned to leadership, scope, and business need.
References
- DAMA International. (2017) DAMA-DMBOK: Data Management Body of Knowledge. 2nd ed.
- Loshin, D. (2013) Data Governance: How to Design, Deploy and Sustain an Effective Data Governance Program. 2nd ed.
- Khatri, V. and Brown, C.V. (2010) ‘Designing Data Governance’, Communications of the ACM, 53(1), pp. 148–152.
- Ladley, J. (2012) Data Governance: How to Design, Deploy and Sustain an Effective Data Governance Program. Elsevier.