Challenge

A leading North Sea operator needed a better way to manage risk across overlapping maintenance projects; both on individual assets and across their wider fleet. Repeated activities, like unnecessary scaffold removal and rebuilds, were driving up costs and compounding operational risk.

The root issue? A lack of visibility. Anomalies couldn’t be easily contextualised, and teams were making decisions without a clear picture of where risks were accumulating.

Solution 

Working closely with the client, we:

• Mapped and assessed their raw data to understand how it was structured
• Applied deep learning to consolidate and visualise risk across the asset
• Created a dynamic model that highlighted where risk was building; based on location, anomaly type, and business-critical parameters

This gave teams a clear, visual understanding of where to focus, when to act, and how to plan smarter.

Impact

With better visibility came better decisions. The client was able to:

• Coordinate work more efficiently
• Reduce duplicated effort
• De-risk operations and maintenance activities

The result? A 10% saving across their O&M budget; and a more confident, connected approach to risk management.