SCA powers sustainable packaging innovation with zero-downtime digital transformation

Transforming critical manufacturing systems with Microsoft technologies

When Svenska Cellulosa Aktiebolaget Containerboard (SCA CB) launched the world’s largest Kraftliner machine at its Obolla mill, the European paper giant needed its technology to match its ambitions. As one of Europe’s leading sustainable packaging producers and largest private forest owner, SCA CB faced a critical challenge: modernising mission-critical systems that power 24/7 operations serving hundreds of customers daily – without risking a single minute of downtime.

SCA’s entire Containerboard operation and supply chain depends on a sophisticated Paper Management System controlling everything from production planning and manufacturing to logistics and invoicing. While stable, this wide-ranging system was built on an aging technology platform that had become a bottleneck to SCA CB’s growth and sustainability ambitions:

• Any downtime would halt production and shipping across multiple facilities

• Limited technical expertise available to maintain the legacy system

• Integration blocked with modern sustainability tracking and SAP cloud systems

• Traditional modernisation approaches estimated 4-5 years minimum, with significant operational risk

With a 2026 factory upgrade deadline and ambitious sustainability goals, SCA CB needed complete transformation with zero operational risk—a challenge that seemed impossible with conventional approaches.

Drawing on a 25+ year partnership, Version 1 and SCA CB collaborated to pioneer an innovative modernisation approach that balanced speed, safety, and business continuity.

“Our longstanding partnership with Version 1 has helped us continually build business value and be more efficient with our operational processes—a key enabler in strengthening the industrial ecosystem that allows us to create the highest possible value from forests.” SCA

We developed a deployment strategy that eliminated the traditional risks of system modernisation:

• Parallel operation: New and legacy systems ran simultaneously, ensuring continuous production

• Module-by-module migration: Gradual transformation maintained full operational capacity

• Instant rollback capability: Any issues could be resolved immediately without production impact

• Database-level integration: Seamless data flow between old and new systems

Advanced AI tools transformed the development timeline while maintaining quality:

• Compressed 20 years of original manual coding effort into under 2 years

• 50% reduction in development time with improved code maintainability

• 63% decrease in time to delivery

Throughout the transformation, SCA CB’s operational priorities remained paramount:

• Zero production interruptions across the entire project

• Preserved familiar user workflows while adding modern capabilities

• Enabled real-time sustainability tracking and environmental impact optimisation

The collaboration delivered transformational outcomes that exceeded expectations:

• 100% operational continuity throughout the entire modernisation
• 10x faster delivery from 20-year estimate to 2-year completion
• Future-ready infrastructure enabling SAP integration and cloud migration
• Eliminated technical debt removed dependency on scarce legacy expertise
• Modern user experience transition to a user-friendly modern web-based portal application
• Strengthened competitive position in sustainable packaging markets

This engagement demonstrates how enterprises can modernise mission-critical systems without operational compromise. By combining deep industry expertise with cutting-edge AI capabilities and innovative deployment strategies, the transformation proves that digital modernisation can accelerate rather than disrupt business growth.

SCA CB now operates with technology that matches its market leadership ambitions, while the methodologies developed during this project are setting new standards for risk-free enterprise transformation across industries.

What began as a 20-year estimate using traditional methods is likely to be accomplished in under 2 years with Microsoft AI-based acceleration approaches Version 1