Cross-agency data efforts often stall long before they produce anything usable, and the constraint is rarely technical. It’s structural: governance that takes too long to operationalize, unclear value for contributors, and processes that introduce more risk and effort than most organizations can sustain.
This case study looks at what changes when those conditions are redesigned. It follows a Tulsa-based initiative that shifted from a slow, centralized model to a more distributed approach, where governance, privacy, and infrastructure were aligned around producing insight quickly and with less burden on participating organizations.
What’s inside The case study walks through the core shifts that made collaboration viable in practice:
Governance structure. How decision-making was scoped and distributed so partners could participate without navigating prolonged approval cycles or unclear authority.
Participation model. How reducing time, effort, and perceived risk changed who was willing to contribute data—and why they chose to return for additional projects.
Privacy approach. How data could be linked and analyzed without exposing direct identifiers, lowering barriers for organizations operating under strict compliance requirements.
Time to insight. What it took to move from multi-year timelines to producing usable outputs within weeks, and how that speed affected momentum across partners.
Sustained use. How the initial project translated into repeatable work, with additional contributors and ongoing data sharing beyond the pilot.