How do you move from reactive HR reporting to proactive, data-driven intervention?
In this session, PostNord Logistics will demonstrate how AI can be applied to a highly relevant and tangible use case: predicting and managing sick leave before it escalates into operational disruption.
By leveraging historical data—capturing trends, seasonality, and behavioral patterns—PostNord builds predictive models that forecast expected sick leave levels across units. These forecasts are continuously compared with actual outcomes in near real time.
This is enabled using Qlik Predict, the native AI capability in Qlik Cloud, allowing fast, scalable model development directly on top of existing data.
The key innovation is not only the prediction, but the automated action layer:

• When actual sick leave exceeds the expected baseline, deviations are detected early
• Qlik Discovery Agents continuously monitor KPIs
• The business is proactively alerted with relevant highlights when metrics start to drift
• HR and operations can intervene before issues escalate and impact performance

This transforms HR analytics from hindsight reporting into forward-looking operational control.
What you’ll take away:

• How to operationalize AI using Qlik Predict on top of existing data foundations
• How to automate monitoring and insights with Discovery Agents
• Turning forecasts into actionable signals within Qlik
• A practical example of moving from insight → action in a real organization

A concrete, high-impact use case—rooted in real demand, built on available data, and designed for immediate business value.