RESEARCH & MODELS
Understand the system
behind the symptoms.
DCI connects the study of data culture with the practical work of governance, organizational learning, and AI readiness.
01 / USAGE AND FLOW
A shared language
for data culture.
The Usage and Flow Data Culture Model (UFDCM) examines two dimensions: how data is used in decisions, and how it moves across teams and boundaries.
Progressive, Preservationist, Traditional, and Protectionist archetypes help practitioners discuss patterns in a defined context. They are lenses for diagnosis, not permanent labels for people.
Apply the model in the companion →Read both axes together.
- Usage
- How is data interpreted and used to make decisions?
- Flow
- Where can data move, and what prevents useful movement?
- Context
- What evidence supports the interpretation for this domain?
02 / GOVERNANCE INTELLIGENCE
Ask what governance
actually changes.
Policies describe intended behavior. Governance intelligence examines enacted behavior, evidence, trust, and drift—so leaders can see where the two align and where intervention is needed.
The companion translates this perspective into baseline assessment, evidence collection, interpretation, and a practical operating cadence.
Explore the reference library →“We value data” is a starting point.
What do people do with it?
A question at the heart of the DCI practitioner approach.
03 / AI READINESS & COGNITIVE ARCHITECTURE
Readiness begins
before the model.
Shared semantics, reliable context, governed flows, and clear human decision authority shape whether AI can operate responsibly inside an organization.
Assess readiness by use case. Connect technical dependencies with cultural conditions, evidence quality, ownership, and human validation.
Watch the AI readiness tutorial →The evolving data architect
Architecture increasingly includes the environment in which people and AI share meaning, memory, and authority.
Explore the Workspace resources →