Power BI Safety Dashboard for Aviation: A Step-by-Step Guide

Infographic showing four key steps to building a Power BI safety dashboard for aviation: connecting data sources, visualizing incidents, customizing dashboards for decision-making, and configuring interactive reports and alerts.

By -Carlos
Posted on April 23, 2025April 23, 2025
Posted in Aviation Safety, Excel, Power BI

Building a Dynamic Safety Dashboard in Power BI for Aviation Operators: A Complete Guide

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 analyze safety data not only reactively but also proactively. This article provides a step-by-step framework to build an advanced, interactive safety dashboard in Power BI, tailored specifically for the needs of Safety Management Systems (SMS) in aviation.

We’ll cover:

Connecting multiple safety and operational data sources
Designing incident categorization 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:

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, or Report_ID.
Scheduled refresh: Use Power BI Service to set refresh intervals (e.g., every 4 hours for safety data, daily for flight hours).

Example Query Logic:

= Table.SelectRows(SafetyData, each ([EventClass] <> "Task" and [ReportStatus] = "Closed"))

Step 2: Structuring Incident Categories and Risk Models with Power BI

Categorizing incidents correctly allows you to move from basic metrics to risk-weighted insights.

Taxonomies to Consider:

ICAO ADREP (standardized event categories)
Operator-specific classifications (e.g., local SOP breaches, fatigue triggers)
Severity and Likelihood Scores (5×5 matrix models)

Implementation Tips:

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
Standardize human error codes, e.g., based on HFACS model

Step 3: Designing the Dashboard Layout

Visual Elements to Include:

Visual	Purpose
Line Chart	Trend of incident frequency per 1,000 flights
Stacked Column	Breakdown by root cause category
Pie/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 Use Case:

Illustrative scenario: An airline safety team noticed a spike in unstable approach reports at a coastal airport during strong crosswinds. Using Power BI’s trend visuals filtered by “Phase of Flight = Approach” and “Location = LCPH,” the team identified that 38% of unstable approaches were clustered within a 2-month period at that airport.

Outcome: The insight leads to a targeted SOP update and refresher training for crews operating into that location.

Note: This is a representative example illustrating how actionable safety insights can be generated. It is not based on a published case study.

Step 4: Customizing for Safety Review Boards (SRBs)

Your dashboard needs to be boardroom-ready and allow for real-time Q&A.

Techniques:

Bookmarks: Predefine views (e.g., last 30 days, last quarter, specific base)
Drill-through pages: Click on 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 or additional mitigations.

Step 5: Configuring Alerts and Interactive Reports

Real-time alerts allow your SMS team to stay proactive.

How to Implement:

Use Power BI Service to create alerts for KPIs (e.g., >3 crew incapacitation in 30 days)
Schedule email reports to Safety Managers weekly
Export visuals as PDF attachments for offline reviews

Integration with Compliance:

Map SRB follow-up actions against EASA Part CAMO/OPS references
Track aging of safety actions using conditional formatting (e.g., red >30 days overdue)

Bonus: Predictive Safety Modeling of Power BI

With enough historical data, Power BI can help you predict emerging risks:

Use time series forecasting on incident trends
Combine flight schedule data + weather + past incidents to predict event likelihoods

Example: A predictive dashboard revealing that the likelihood of bird strikes doubled during pre-dawn hours in a specific region, prompting the airport to enhance wildlife control before morning departures.

Source: Inspired by real-world bird strike trend analyses conducted by European and North American airport authorities. No proprietary data disclosed.

Conclusion

With the right tools and structure, Power BI can transform aviation safety oversight. By integrating live data, customizing for decision-makers, and leveraging predictive capabilities, aviation operators can move from reactive compliance to a proactive safety culture.

The implementation is both accessible and impactful: even a basic dashboard with trend and category visuals, refreshed daily from Excel, can reveal high-risk patterns and drive immediate safety interventions.

If you’re ready to evolve your aviation safety analytics, let’s build your dashboard together.

Carlos FC