Proposal: Dual-Head Leadership Model for Data & Analytics

Purpose

To provide a clear, sustainable leadership structure for the Data & Analytics function by separating accountability for:

  • Data engineering and analytical foundations, and
  • Reporting and analytics delivery

while maintaining shared ownership of standards and governance.

This model is intended to:

  • reduce delivery risk
  • improve clarity of ownership
  • strengthen alignment with business priorities
  • support growth of the function without dependency on a single role

Context

The Data & Analytics function currently spans:

  • Data acquisition and integration
  • Data modelling and analytical foundations
  • Reporting and analytics delivery
  • Stakeholder engagement and prioritisation
  • Standards, governance, and quality

These responsibilities place competing demands on a single leadership role:

  • long-term technical coherence
  • short-term delivery outcomes
  • stakeholder confidence
  • operational rhythm

To reduce strain and increase effectiveness, leadership is best structured around two complementary Head-of roles.


Proposed Roles

1. Head of Data Engineering & Analytics

Primary accountability:
To ensure the organisation’s data and analytical foundations are technically sound, coherent, and sustainable.

Architecture & Data Foundations

  • Define and maintain the overall data and analytical architecture.
  • Own the Common Data Model and domain design.
  • Set integration and transformation patterns across data sources.
  • Ensure consistency of data structures across business areas.

Data Engineering Standards & Quality

  • Establish and uphold standards for:
    • data modelling
    • transformation
    • analytical structures
  • Ensure strong data quality, lineage, and traceability.
  • Protect the technical integrity of the data platform.

Platform & Capability Evolution

  • Lead the strategic evolution of the data platform.
  • Balance short-term delivery needs with long-term sustainability.
  • Identify future capability requirements and shape technical direction accordingly.

Technical Enablement & Coaching

  • Provide technical leadership to engineers and analysts.
  • Promote reuse through patterns, exemplars, and guidance.
  • Coach and mentor to build long-term capability within the team.

Shared Standards & Governance

  • Work jointly with the Head of Reporting & Analytics Delivery to:
    • apply data and analytics standards
    • uphold consistent definitions
    • ensure quality and assurance
  • Embed governance as an enabling function rather than a barrier.

Primary question owned:

Is what we are building technically sound, analytically coherent, and sustainable?


2. Head of Reporting & Analytics Delivery

Primary accountability:
To ensure that business reporting and analytics requirements are understood, prioritised, and delivered through strong stakeholder relationships and a clear delivery operating model.

Key responsibilities:

Stakeholder Enablement

  • Establish and maintain effective working relationships with senior stakeholders outside the Data & Analytics function.
  • Act as the primary interface between business functions and the reporting & analytics teams.
  • Translate business objectives into reporting and analytical outcomes.
  • Manage expectations around scope, timing, and delivery trade-offs.
  • Promote shared ownership of analytical products with report sponsors and business owners.

Business Requirements Management

  • Collect, structure, and maintain the organisation’s reporting and analytics requirements.
  • Ensure requirements are:
    • clearly defined
    • prioritised
    • traceable to business needs
  • Own the reporting demand intake process and backlog.
  • Balance short-term reporting needs with longer-term analytical development.
  • Ensure requirements are expressed in a way that enables consistent and reusable delivery.

Delivery & Visibility

  • Own the delivery cadence for reporting and analytics products.
  • Coordinate sequencing and dependencies across teams.
  • Ensure progress, risks, and priorities are visible to stakeholders.
  • Drive adoption and effective use of reports and insight.

Shared Standards & Governance

  • Work jointly with the Head of Data Engineering & Analytics to:
    • apply data and reporting standards
    • uphold consistent definitions
    • ensure quality and assurance
  • Embed governance into delivery without creating unnecessary friction.

Primary question owned:

Do we clearly understand what the business needs from reporting and analytics, and are we delivering it in a visible and controlled way?


Shared Responsibilities

The two roles jointly own:

  • Standards for data and analytics
  • Definitions and quality thresholds
  • Governance and assurance
  • Alignment with organisational policy

Governance is positioned as:

an enabling function that supports delivery and trust, not a barrier to progress.


Operating Model

AreaHead of Data Engineering & AnalyticsHead of Reporting & Analytics Delivery
Architecture & models
Data foundations
Standards & integrity✔ (shared)✔ (shared)
Reporting & insight delivery
Stakeholder relationships
Requirements management
Prioritisation & sequencing
Long-term platform direction
Delivery cadence & visibility

Decision rights are explicit:

  • Architecture and data design sit with Engineering & Analytics
  • Delivery sequencing and stakeholder commitments sit with Reporting & Delivery
  • Overlapping decisions are aligned jointly before communication

Benefits

For the organisation

  • Reduced dependency on one individual
  • Clearer ownership of outcomes
  • Stronger alignment between architecture and delivery
  • Improved predictability and transparency

For stakeholders

  • Single narrative on priorities and progress
  • Stronger engagement and working relationships
  • More consistent definitions and reporting

For the team

  • Clear leadership lanes
  • Reduced friction and rework
  • Stronger technical foundations
  • More visible direction

Risk Mitigation

This model avoids:

  • role overlap
  • design by committee
  • bottlenecks caused by over-centralisation
  • delivery driven without architectural control

It balances:

  • pace (delivery)
  • with shape (architecture and standards)

Leave a Comment