How Stora Enso enables autonomous data teams with dbt
last updated on Dec 18, 2025
Stora Enso, a Finnish-Swedish renewable materials company with 19,000 employees across Europe, Asia, and South America, is a leader in the transition from fossil-based to renewable materials. The company's five divisions each serve distinct markets with unique operational requirements.
But Stora Enso's centralized data team struggled to keep pace with growing demands, which created months-long delays that slowed decision-making across the organization. By implementing dbt as the foundation for decentralized data operations, Stora Enso transformed delivery times from months to days and enabled true self-service analytics.
Centralized bottlenecks slow the business
| Challenges | Impact |
|---|---|
Two-month minimum lead times | Even small changes took months to deliver |
Knowledge retention problems | Central team couldn't maintain expertise across 5 divisions |
Mounting backlogs | Divisions competed for limited central resources |
Context switching | Team constantly explaining business basics instead of delivering insights |
"Regardless of how big the central team is, there are not enough people just to retain the business knowledge," reflects Jiri Bjalek, Data Platform Team Leader at Stora Enso.
Strategic shift requires the right technology foundation
Recognizing that scaling the centralized team wasn't the answer, Stora Enso made a decisive organizational change three years ago:
- Cut the central data team in half by moving engineers directly into divisions
- Transformed the central team from service delivery to platform provision
- Empowered divisions to prioritize their own analytics projects
"We are essentially owning just the platform," says Jiri. "We're responsible for making sure it provides all the features for divisional teams to build their data products."
This organizational shift revealed a critical problem: Stora Enso's existing data transformation tool, WhereScape, wasn't designed for autonomous team operations. The platform needed to be accessible enough for diverse teams to use independently, yet robust enough to maintain enterprise standards. While exploring alternatives, Stora Enso discovered dbt.
| WhereScape challenges | dbt's solution |
|---|---|
Steep learning curve with templates | SQL as universal language all analysts knew |
Specialized knowledge required | Organic adoption without retraining |
Framework-first thinking | Direct pipeline logic development |
Limited divisional adoption | Easy spread across organization |
"The big benefit is that dbt uses the SQL language," says Jiri. "SQL has been the de facto standard for many data analysts over decades already, and that was the main success factor; it was so easy to spread it in the organization."
Beyond SQL accessibility, the dbt platform brought built-in data lineage and testing frameworks that helped maintain quality standards across autonomous teams.
Self-service analytics delivers speed
With dbt as the foundation, the organizational shift delivered immediate and measurable improvements across all divisions:
| Before | After |
|---|---|
Two-month minimum lead times | Daily updates and rapid iteration |
Centralized team overwhelmed | Self-service analytics across 5 divisions |
Business knowledge bottlenecks | Direct business-to-analyst collaboration |
Divisions competing for resources | Platform team focused on infrastructure |
"They have their own teams now and can prioritize their own priority projects," explains Jiri. "It's much, much easier for them to run projects nowadays."
Building for governance and AI innovation
The success of the decentralized model has positioned Stora Enso to tackle more ambitious goals. The company continues to evolve its data operations with an eye toward future compliance and innovation requirements:
- EU regulatory compliance and ISO 27001 certification preparation
- AI integration exploration built on solid data foundations
- Platform portability through a successful Databricks proof-of-concept
Stora Enso's approach demonstrates how the right platform choice can enable profound organizational change. By shifting from centralized service delivery to decentralized self-service, Stora Enso solved its fundamental challenge of scaling data operations while maintaining quality and consistency.
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