Rail asset performance

A spell of reduced asset performance created the requirement for a data-driven review of asset failure and associated delay minutes.

Our Solution

A Power BI tool that links multiple datasets and analyses performance patterns and trends.

A detailed review of key trends, locations and asset types.

Recommendations ont how to resolve ongoing data issues to enhance future capability of the tool.

Features and Benefits

A user-friendly tool that provides multi-level analysis down to individual incidents.

Multiple performance metrics that quantify incident characteristics, such as duration and the number of services affected.

A dynamic trend scoring system to prioritise and drill-through to deeper analysis.

Robust location and asset-type hierarchies that can be used for drilling up and down.

Incidents are categorised into major and minor incidents, which means trends can be identified by excluding data-obscuring major incidents from analysis.

The identification of individual assets that repeatedly fail and how they fail.

Delay mapping to identify performance hotspots.

The tracking of lead indicators to highlight potential future performance impact.

Risk forecasting to compare asset failure rate to the maintenance schedule, highlighting assets that are “due” to fail.

Outcome

The Power BI tool was incorporated into business as usual and continues to provide analysis of the latest data. The new data-driven approach was welcomed by the rail operator and the recommendations are currently being considered.