As part of its strategy, Keva, the Finnish public sector pension provider, decided to strengthen its data foundation to better leverage analytics, automation and AI. Arked helped Keva to create clear Data and AI leadership structure, define data and AI goals as part of enterprise strategy and design a data governance model with clearer ownership, roles and ways of working.
Building a stronger AI-ready data foundation
As part of its strategy, Keva, the Finnish public sector pension provider, decided to strengthen its data foundation to better leverage AI, analytics, automation. Arked helped Keva to define long term AI and data goals, create clear Data and AI leadership structure and design a modern data governance model with clearer ownership, roles and ways of working.
The challenge
Keva has a long history of leveraging data in its business and had strong expertise and technological foundations in place. Also AI adaptation journey had started with Copilot tools and AI pilots.
However, Keva’s data and AI operations were managed largely as a support function, with no data and AI leadership role and also development and governance responsibilities spread across different parts of the organization.
Without clear Data and AI leadership, long-term strategic goals and road maps did not exist and shared data and AI capability development was lagging behind. Also there was no shared Data Governance framework and business-driven data ownership was lacking. This meant data was not always easy to use across business and it was missing key metadata important both for business and AI utilization.
As part of its strategy, Keva decided to remodel their AI and data leadership and strengthen its data foundation to better leverage AI, analytics, automation and .
Arked solution
Arked provided senior-level expertise from the start to build a strategic AI-ready data foundation. Arked responsibilities included:
- Current and target state analysis
- Define enterprise-wide data goals for enterprise strategy
- Identified need to create more clear AI-goals and road map
- Data and AI leadership framework and role design
- Modern data governance design
- Implementing data product development methods
- Supporting the implementation
Results and next steps
- Enterprise-wide data strategy was approved by the leadership team
- Data and AI leadership role and organization model were defined and resourced
- Data governance pilot was completed to test framework and improve data quality
- Data product framework implementation is currently ongoing one business unit at time
Client feedback: 10 / 10
“We are more than happy with the expertise and results Arked provided.”
Tommi Heinonen, CIO, Keva
