Templates

Using templates speeds up occurrence processing. As there are usually many occurrences that fall under the same type of incident, templates can be predefined in the Safety Quality App. Once a template has been selected, the occurrence will be automatically populated by the app with predefined set of information. This information can include classifications and specific text to certain fields.

Smart templates

By using smart templates, the app will automatically select a template that will be applied when preprocessing occurrences. Selecting the template is based on predefined rules that can be customized. An example of a rule: word "bird" is mentioned in the title of the occurrence and "Birdstrike" template will be used that will classify the event as a birdstrike.

Use case examples

• Anonymizes: remove aircraft registration from title and description of the event to reduce processing workload

• Corrects mistakes: remove redundant leading and trailing spaces in aircraft registration to enable automated data retrieval from an aircraft registry

• Harmonizes data: for example replaces “Helsinki” in location of occurrence by “EFHK” ICAO code to allow business intelligence tools to pinpoint hotspots for specific types of incidents

Use case examples

• Adds aircraft information from an Excel sheet, based on a national aircraft registry

• Adds weather report at the time of the event from a weather service provider's API

• Adds flight data from a flight information API

• Set fixed values to specified fields for compliance reasons

• Import data to E2 from Excel as a batch operation

Processing of occurrences can be shared among personnel processing the occurrences. Safety Quality App can share the workload among persons working on occurrences by predefined percentages.

Classifying occurrences in multiple Eccairs classes is a great use case for machine learning. A model will be created by using historical data on how occurrences have been classified and based on this model a high accuracy of correct classifications can be predicted. As the classifications in the Eccairs taxonomy are complex and thus the classifications selected by the reporter are usually not correct, machine learning can provide a good prediction for the occurrence processor and reduce the workload needed to reclassify the occurrence.

• Add your own templates to the application

• Modify existing templates to match your needs

• Customize the app to meet your workflow

Want to learn more or see a demo? Let's schedule a session!