From Reactive Reporting to Proactive Controlling: Lessons from Zavarovalnica Sava

Insights from the 21st Adriatik Controlling Conference

At this year’s 21st Adriatik Controlling Conference, dedicated to the modernization of controlling, one session stood out. Matic Hren, Information Solutions Architect at Zavarovalnica Sava, took the stage to walk a room full of finance and controlling professionals through a real-world case study: how a single infrastructure decision fundamentally changed the quality and timeliness of business decision-making and why it matters for any large organization.

A bottleneck you’ll recognize

Zavarovalnica Sava, Slovenia’s second-largest insurer and the parent company of the international Sava Insurance Group, was facing a challenge familiar to many complex organizations. ETL processes were slowing down, and data was reaching the warehouse with a six- to eight-hour lag. The existing architecture performed full nightly reloads from core systems. An approach that was becoming increasingly unsustainable as business volumes grew and the group expanded into new markets.

The controlling and business intelligence teams felt the impact most acutely. Most of their time was consumed by waiting for data, validating completeness, and producing backward-looking reports, leaving little room for genuinely value-adding analysis.

Sound familiar? You’re not alone.

The fix: Change Data Capture

The Zavarovalnica Sava team found the answer within their existing toolset. They were already using Qlik Talend as their primary integration and orchestration platform, which they extended with Qlik Replicate,  a tool built on Change Data Capture (CDC) technology. Rather than moving entire datasets on a schedule, CDC reads transaction logs and pushes only the records that have actually changed into the analytics environment.

The results were immediate and measurable: data latency dropped from several hours to under 15 minutes. The analytics layer now operates in near-real-time sync with core systems, and the platform reliably processes up to 400 million row-level changes per month across individual tables.

What this means for controlling

The technical shift translated directly into business impact. Hren illustrated the contrast clearly:

• Before: nightly batch processing, backward-looking reports, manual reconciliations, and constant waiting for data.
• After: near-real-time data flows, immediate anomaly detection, proactive corrective action, and a genuine focus on advanced analytics and AI-driven models.

Prior to the change, Hren estimated that controlling teams were spending up to 80% of their time managing historical data. The goal, which they achieved, was to invert that ratio: 80% of capacity redirected toward advanced analytics, model development, and strategic guidance.

Delivered in under a year

The project ran across four phases, from proof of concept through to full production deployment, including group-wide system integration, and was completed in under twelve months. The solution is largely configuration-driven with minimal coding required, yet flexible enough for advanced setups. Hren highlighted ease of implementation as one of the key factors behind both the pace and the success of the rollout.

Modernization starts at the foundation

The Zavarovalnica Sava story makes a compelling case that controlling modernization rarely begins with dashboards or reports. It begins deeper, with the data infrastructure that feeds them. Eliminate the data lag, and you eliminate the decision lag that follows.

If this resonates with challenges you’re facing and you’d like to explore what a similar transformation could look like in your organization, get in touch. Our specialists are happy to walk you through the options best suited to your environment and help you take the first step.