Data Product Operating Model™
Operating data products at enterprise scale requires clear ownership, industrialized build, active governance and a route to AI consumption. This model defines the roles, rituals and capabilities required.
This framework operationalizes the highlighted layers of the Data Tiles Decision-Driven Enterprise operating model.
- Data products are launched as projects, not operated as products.
- Roles and rituals are unclear. Ownership defaults back to IT.
- Scaling means rebuilding the platform every two years.
- Clear roles: business owner, product steward, platform team.
- Industrialized build path that does not require replacing existing tooling.
- Active governance and AI-readiness built into the operating model from day one.
- Stage 1
Roles and Accountability
Define and assign the business owner, product steward and platform roles.
- Stage 2
Industrialized Build
Use a repeatable build pattern that works with your current stack.
- Stage 3
Active Governance
Governance is part of the product, not a downstream review.
- Stage 4
AI Consumption
Design products from the start to be consumed by AI safely.
- · Product thinking is theoretical, not operational.
- · Owners do not have the tooling to take real accountability.
- · Governance and AI readiness are afterthoughts.
- Latttice provides the industrialized build path with governance and ownership built in.
- Our advisory teams help define the operating model and roles.
How Latttice and Lenz Work Together
Understand how the trusted-data layer and the decision-and-AI layer combine to deliver active governance and AI readiness end to end.
How to Use Latttice Without Replacing Your Existing Stack
Industrialize trusted data products and active governance on top of the platform you already have.
Talk to us about applying this framework.
We help executives sequence the work, prove value early and scale with Latttice and Lenz where it matters.