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Safety Intelligence and SMS

Leveraging the Power of Predictive Data

Safety Intelligence and SMS

Safety Intelligence

Managing risk through Safety Management Systems (SMS) is now standard throughout the aviation industry worldwide. By gathering insight through various activities and data sources, SMS allows operators to accurately evaluate risk. Utilizing a systems approach promotes risk assessment through analysis, improving safety. Acting as a system, SMS manages safety with the same level of priority as other core business processes.


A successful SMS relies on data. Aviation operations will experience practical drift, meaning an operation has drifted away from procedures and risk controls as they were intended. Accepting this tendency, monitoring for drift through SMS data becomes the operation’s primary defense.


Using SMS-derived data to create safety intelligence, an operation can detect and manage future risks. We can define safety intelligence as the result when the data generated by the SMS is used to generate predictive analysis. By following data trends, safety managers can forecast risk and manage it appropriately, preventing unfavorable events.

Consistent Data Collection
To create safety intelligence, operations must collect valid data consistently. Consistent participation in safety reporting by all staff members is a critical element for data collection. Reports must use a standard format to ensure all data is accumulated accurately. The information communicated in each report should contain as much detail as possible. A quick report is not necessarily better than none.


Data can be collected from a variety of different areas, including flight safety reports, ground safety reports, security reports, incident reports, flight risk analysis/assessment tools (FRAT), and Internal Evaluation Program (IEP) checklists. Every time a report or checklist is submitted, the operation adds data to their SMS, providing increased opportunity for predictive analysis.
When collecting data, divide risks into common areas and assess it with consistent measurement. Practicing precise risk measurement is essential to the development of accurate trends. Discovering trends increases the opportunity to identify precursors to an unfavorable event.


Data should also be collected with an eye toward historical recording. Reliably collecting data over long periods of time allows comparison of monthly and yearly trends. This enables a safety manager to monitor performance over extended periods.

Reactive, Proactive, and Predictive Data
The data developed by the SMS is characterized in three ways: reactive, proactive, or predictive.


Generating reactive data involves analysis of past outcomes or events. Hazards are identified through investigation of safety occurrences. Incidents and accidents are an indication of system deficiencies and therefore can be used to determine which hazard(s) contributed to the event.


Generating proactive data involves collecting safety data of lower consequence events or process performance and analyzing the safety information or frequency of occurrence to determine if a hazard could lead to an accident or incident. The safety information for proactive hazard identification primarily comes from flight data analysis (FDA) programs, safety reporting systems and a safety assurance function like an internal evaluation program. Proactive data collection presents a clear advantage, identifying risk exceedances and occurrences before an undesirable event happens.


An operation gains predictive data, or safety intelligence, from the aggregation of reactive and proactive data to facilitate predictive analysis. Managing data appropriately throughout this process is necessary for accurate results. This is best accomplished using software applications designed specifically for data management, analysis, and presentation.


While past performance is not a guarantee of future results, identifying trends and drawing attention to risk and performance levels can improve decision-making.


Safety management systems assess and define the risk factors for flight operation. What operations do with the information determines if the data is reactive, proactive, or predictive.


PRISM Safety Intelligence
PRISM ARMOR presents aggregated data, displays performance trends, and shows predictive risk forecasts in its analytic interface called Safety Intelligence. Individual specific safety performance indicators (SPIs) are actively tracked, with email alerts for risk threshold exceedances. PRISM ARMOR collects and organizes data then feeds it to Safety Intelligence for processing into visual dashboard reports where safety managers easily identify trends and predictive risks.


PRISM specializes in aviation safety and the role of risk management in avoiding costly accidents. Combining PRISM ARMOR SMS software with ARGUS expert training provides aviation safety managers with tools and expert resources to build their safety intelligence.

Written  By:

JR Russell

Executive Vice President, PRISM

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