Austrian Universities kpi analysis & ewr report

An interactive Power BI dashboard. It benchmarks three major universities through various KPIs and detects early warning signals for financial stability.

Slide 1

Main KPI for each Strategic Dimension

An interactive Power BI solution designed to benchmark university performance and visualize strategic KPIs against peer institutions.

Overview & Early Warning System

The main dashboard with top-level metrics across all dimensions, featuring automated early warning signals for at-risk KPIs.

Slide 3

EWR Details – Risk Indicators & Thresholds

Analysis of critical stability metrics: P&L, Equity Ratio, and Mobility

Slide 4

Secondary Metrics & Trends

Displays additional metrics for each dimension. The charts show trends and growth percentages.

Slide 5

See More – Single KPI Fact Sheet

A complete profile for a single KPI. It includes the definition, formula, and detailed charts.

Overview

Austrian Universities KPI & EWR Report is a strategic intelligence tool developed to transform static university data into actionable insights. It benchmarks performance across three major institutions (UIBK, WU Vienna, Vienna University) to support decision-making in compliance with federal funding requirements (New Public Management). The project consolidated fragmented Excel datasets into a robust Power BI model, enabling real-time tracking of 30+ KPIs across Teaching, Research, and Finance. It bridges the gap between raw administrative data and strategic management.

Role: Data Analyst & Dashboard Designer
Year: 2026

The challenge

University management relies on strict reporting standards to secure government funding. However, the existing data landscape was highly fragmented, trapped in disconnected Excel tables that made peer comparison impossible. Our challenge was to build a scalable, automated system that could not only visualize current performance but also flag risks.

Steps

1

Strategy & KPI Definition

Defined 6 strategic dimensions (e.g., Research, Social Responsibility) and selected 30 critical KPIs aligned with federal performance agreements.

2

Data Architecture (ETL)

Transformed fragmented tables into a Star Schema. Used Power Query M-code to remove non-contiguous noise rows and standardize the dataset.

3

Advanced Modeling (DAX)

Built the system’s “brain” using complex DAX measures (REMOVEFILTERS, Time Intelligence) to calculate Peer Comparisons and YoY Growth.

4

UX & Interactivity

Designed an app-like experience with a fixed sidebar, bookmark-driven pop-up panes, and drill-through logic for deep analysis.

5

Infrastructure & Security

Deployed the environment on Mac M1 via virtualization and configured Shareable Cloud Connections (OAuth2) to enable secure team collaboration.

results

The project successfully centralized university data into a single source of truth, replacing manual reporting with automated insights. The Early Warning System (EWR) now automatically flags financial risks (e.g., Equity Ratio drops), allowing management to react before critical thresholds are breached. Technically, the solution proved that enterprise-grade Power BI development is viable on Apple Silicon infrastructure, and the custom Gateway configuration restored the team’s ability to collaborate in the cloud without data conflicts.

Core Features

  • Dynamic Peer Benchmarking (DAX): Custom DAX measures utilize CALCULATE and ALL functions to dynamically compare the target university’s performance against the calculated average of peer institutions.

  • Time-Intelligence Engine: Implements advanced logic using REMOVEFILTERS to “look back in time,” enabling automated Year-over-Year (YoY) growth calculations without manual data restructuring.

  • Smart Context Integration: A robust 1-to-many relationship links the quantitative master table to a qualitative “WP4” dataset, ensuring definitions and strategic context update instantly upon interaction.

  • App-Like Navigation & Drill-Through: Replaces static report pages with a fixed sidebar and bookmark-driven pop-up panes, allowing users to “drill through” from high-level summaries to granular detail pages.

  • Programmatic KPI Flagging: Utilizes a custom isMain column flag within the standardized dataset to programmatically identify and project “Headline KPIs” onto executive overview dashboards.