If your data strategy isn’t delivering business impact, it’s time to rethink the Data Operating Model (DOM) behind it.
We often focus on tools and platforms, but without the right DOM, even the best data strategies struggle to scale, govern, or generate ROI. DOMs align strategy with execution—embedding governance, literacy, and data quality across the enterprise.

Five Proven DOM archetypes:

1.- Descentralized – Domain-led, mesh-style team
 ▪️ Pros: Flat, aligned with lines of business
 ▪️ Cons: Ownership gaps, legal risk
2.- Network – RACI-based structure layered over decentralization
 ▪️ Pros: Clarifies roles, retains flexibility
 ▪️ Cons: Complex to maintain
3.- Centralized – One team owns all
 ▪️ Pros: Speed, control
 ▪️ Cons: Low agility, tough for transformation
4.- Hybrid – CoE leads, domains execute
 ▪️ Pros: Best-practice factory
 ▪️ Cons: Hard to align, costly
5.- Federated – Subsidiaries empowered with central governance
 ▪️ Pros: Works at global scale
 ▪️ Cons: Requires maturity and resources

There’s no perfect model—just the one that best fits your size, culture, regulation, and maturity. DOMs should evolve: start lean, then grow as literacy, tech, and governance mature

Practitioner Takeaways: 
 • Anchor in a problem-back value story
• Publish a one-page DOM charter: integration, funding, accountability
 • Pilot federated or network models before scaling
 • Build trust by staffing CoEs with rotational talent
 • Track both data KPIs (e.g., completeness, timeliness) and business KPIs (e.g., ROI, forecast uplift)

Which model are you using? What’s working—and what’s not? Let’s elevate the conversation.