Introduction
In the aviation industry, data-driven safety management isn't just a luxury — it's a necessity. With increasing regulatory expectations from authorities like EASA and ICAO, operators must analyse safety data not only reactively but also proactively.
This guide provides a step-by-step framework to build an advanced, interactive safety dashboard in Power BI, covering:
- Connecting multiple safety and operational data sources
- Designing incident categorisation models (e.g. ADREP taxonomy)
- Creating custom risk metrics
- Configuring actionable visuals and alerts for real-time decision-making
This guide is built for aviation safety analysts, compliance managers, and safety officers looking to elevate their digital toolkit.
Step 1: Connecting your data with Power BI
Example scenario: You receive weekly exports from your SMS tool (e.g. Coruson) and monthly maintenance data from AMOS.
Tools required
- Power BI Desktop
- Power Query
- Excel/CSV, SQL Server, or SharePoint List integrations
Best practices
- Create a data staging area: Clean and transform your CSVs into structured tables. Use Power Query to combine multi-source files (incident reports, flight logs, maintenance issues).
- Create relationships: Link tables using unique keys such as
Flight_Number,AC_Reg, orReport_ID. - Scheduled refresh: Use Power BI Service to set refresh intervals (e.g. every 4 hours for safety data, daily for flight hours).
Example Power Query filter logic:
= Table.SelectRows(SafetyData, each ([EventClass] <> "Task" and [ReportStatus] = "Closed"))Step 2: Structuring incident categories and risk models
Categorising incidents correctly allows you to move from basic metrics to risk-weighted insights.
Taxonomies to consider
- ICAO ADREP (standardised event categories)
- Operator-specific classifications (e.g. local SOP breaches, fatigue triggers)
- Severity and Likelihood Scores (5×5 matrix models)
Implementation
Create a calculated column in Power BI for risk score:
RiskScore = [Severity] * [Likelihood]Build a slicer to filter incidents by: Phase of Flight, Aircraft Type, Operator Base. Standardise human error codes using the HFACS model where applicable.
Step 3: Designing the dashboard layout
| Visual element | Purpose |
|---|---|
| Line chart | Trend of incident frequency per 1,000 flights |
| Stacked column | Breakdown by root cause category |
| Donut chart | % of events by fleet or base |
| Heatmap | High-risk areas on routes or locations |
| Matrix table | Drill-down of events by SRB month and action owner |
Example: A safety team noticed a spike in unstable approach reports at a coastal airport during strong crosswinds. Filtering by "Phase of Flight = Approach" and "Location = LCPH," they identified 38% of unstable approaches clustered within a 2-month period — leading to a targeted SOP update and refresher training.
Step 4: Customising for Safety Review Boards
Your dashboard needs to be boardroom-ready and allow for real-time Q&A during SRB sessions.
Key techniques
- Bookmarks: Predefine views (e.g. last 30 days, last quarter, specific base)
- Drill-through pages: Click an event and show full details — narrative, reporter details, follow-up action
- Measure toggles: Allow switching between frequency and risk-weighted scoring
Advanced tip: Use What-If Parameters to simulate the impact of increased reporting volumes or additional mitigations.
Step 5: Configuring alerts and interactive reports
Real-time alerts allow your SMS team to stay proactive rather than reactive.
Implementation
- Use Power BI Service to create alerts for KPIs (e.g. >3 crew incapacitations in 30 days)
- Schedule email reports to Safety Managers weekly
- Export visuals as PDF attachments for offline SRB reviews
Compliance integration
- Map SRB follow-up actions against EASA Part CAMO/OPS references
- Track ageing of safety actions using conditional formatting (red = >30 days overdue)
Bonus: Predictive safety modelling
With enough historical data, Power BI can help you predict emerging risks using time series forecasting on incident trends, combined with flight schedule data, weather, and past incidents.
Conclusion
With the right tools and structure, Power BI can transform aviation safety oversight. By integrating live data, customising for decision-makers, and leveraging predictive capabilities, aviation operators can move from reactive compliance to a proactive safety culture.
Even a basic dashboard with trend and category visuals, refreshed daily from Excel, can reveal high-risk patterns and drive immediate safety interventions.