
I build end-to-end analytics solutions that translate data into decisions for commercial, financial, and management teams.
I translate business questions into clear metrics and decision frameworks, ensuring analytics directly supports real outcomes, not just reporting.
Anchor analytics in real business and financial decisions.
Translate ambiguity into clear metrics and success criteria.
Frame problems before building solutions.
Align stakeholders on what matters and why.
Avoid vanity dashboards and metric overload.
I take responsibility for analytics outcomes, ensuring metrics are owned, governed, trusted, and consistently used in real decision-making.
Establish metric ownership and governance to keep analytics consistent at scale.
Align KPI definitions with business and financial decision needs.
Drive adoption through clarity, documentation, and accountable delivery.
Experience delivering analytics across commercial performance, marketing effectiveness, and financial reporting, with a strong emphasis on data governance and accuracy.
Worked with analytics contexts influenced by central banking, healthcare, commercial and financial regulation.
Built reporting and analytics involving sensitive and personal data, with strong emphasis on controls and data protection.
Designed KPI frameworks used by leadership across finance, operations, and digital marketing functions.
Owned and built from scratch the largest analytics data model in the healthcare domain (ELM Data model), for a department with DKK 4bn+ revenue, becoming the single trusted data foundation for pricing, commercial performance, and C-level decision-making.
Pioneered BI data governance and metric ownership in healthcare, establishing KPI definitions as a single source of truth and reducing metric misalignment.
Embedded AI-assisted insights into reporting pipelines, reducing ad-hoc analysis requests by ~20-30% and cutting decision turnaround time.
Automated financial and operational reporting, removing ~20–40 hours/month of manual effort through KPI-triggered delivery.
I define and maintain the analytics data layer, turning complex and fragmented data into scalable, decision-ready models that teams can trust.
Build and maintain a reliable analytics data layer.
Design business-friendly models aligned with financial and operational logic.
Standardize KPIs and definitions across teams.
Ensure data models scale with business growth and reporting demands.
I automate analytics delivery and apply AI where it meaningfully improves speed, clarity, and communication, without adding operational complexity.
Automate recurring reporting, data preparation, and delivery workflows.
Use AI-assisted tools to accelerate analysis, documentation, and presentation.
Reduce manual effort while maintaining reliability and control.
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