Data Strategy
We design team structures, roles, and operational processes that sustain a data-driven culture across the enterprise — turning strategy into daily practice.
Our approach
DAI Consultancy designs data operating models that reflect each organisation's scale, industry, regulatory context, and culture. We evaluate three primary archetypes — centralised, federated, and decentralised (data mesh) — and recommend the hybrid model that best balances enterprise control with domain agility. For large conglomerates and government entities common in the GCC, we frequently implement federated models where a central team sets standards and provides shared infrastructure while domain teams retain ownership of their data products.
The operating model design covers four interconnected layers. The strategic layer defines executive accountability (CDO or equivalent), data council composition, and strategic priorities. The tactical layer establishes domain data ownership, stewardship networks, and cross-functional working groups. The operational layer specifies how teams collaborate on daily tasks — data quality remediation, incident resolution, pipeline development, and analytics delivery. The enabling layer defines the technology platforms, tools, and self-service capabilities that support all three layers above.
A critical component is role definition and career pathing. We work with HR teams to create formal job descriptions, competency frameworks, and career paths for data roles — data stewards, data engineers, analytics engineers, data scientists, and governance professionals. In a market where data talent is scarce, formalising these roles is essential for both recruitment and retention across GCC organisations.
What's included
A comprehensive design document covering organisational structure, team composition, reporting lines, and interaction patterns for data capabilities.
A responsibility assignment matrix clarifying who is Responsible, Accountable, Consulted, and Informed for every key data management activity.
Formal job descriptions, competency frameworks, and career progression paths for all data roles — from steward to CDO.
Terms of reference for data governance councils, including membership, meeting cadence, decision authority, and escalation procedures.
A phased plan for evolving from the current organisational state to the target operating model, with change management activities at each stage.
Want to scope this for your organisation?
Discuss an Operating Model DesignRegional framework alignment
We map this service to the official data governance, privacy, security, sharing, and operating-model expectations that apply in each jurisdiction.
Background
An operating model defines how an organisation structures its data capabilities — the teams, roles, processes, decision rights, and governance mechanisms that determine how data is managed, governed, and used on a daily basis. Without a deliberate operating model, data initiatives rely on ad hoc arrangements that cannot scale. For GCC enterprises building permanent data capabilities, the operating model is what separates a one-time project from a sustainable competitive advantage.
Use cases
Designing federated data operating models for national data authorities that coordinate governance across ministries while respecting departmental autonomy.
Restructuring data teams within banking groups to create domain-aligned data product teams with clear ownership and accountability for data quality.
Building shared data services organisations that serve multiple business units with common platforms and standards while allowing sector-specific flexibility.
Related services
FAQ
A data operating model defines how an organisation structures its data capabilities: the teams, roles, processes, decision rights, and governance mechanisms that determine how data is managed and used daily. It is the organisational design that makes data strategy executable.
It depends on your scale, complexity, and culture — there is no single right answer. Larger, multi-entity organisations often benefit from a federated model, where a central team sets standards and domain teams own their data, while smaller organisations are often better served by a lean, centralised team. DAI helps you find the right balance.
We work closely with HR and leadership teams to define new roles, create career paths, and develop transition plans that bring people along. Operating model changes succeed when employees understand their new roles and see opportunities for growth.
Let’s discuss how our governance-first approach to operating model design can accelerate your data and AI initiatives.
