Developments in deep data analytics offer huge potential to find new routes for optimising performance, enhancing decision making and connecting operations.
As the Internet of Things (IoT) continues to grow, the volume and speed of data being generated is overwhelming. The potential for useful insights is greater but those insights can be drowned in the flood of data. With artificial intelligence and data analytics, tremendous volumes of operational and external data can now be distilled and analysed to provide relevant, timely and actionable information that empower companies to make better, more informed decisions.
Greater reliability, higher levels of confidence and better outcomes
At Wood, we are harnessing the power of data analytics and machine learning to help our clients make smarter decisions in high-risk situations.
We have developed an AI-enabled Decision Support System, together with a large energy corporation, that analyses large data streams to help inform decision making based on certain thresholds being exceeded. Clients can now instantly assess the risk to their operations in a given situation and immediately take the most appropriate action – saving time and money.
Working with a third party experts, we have used artificial intelligence to understand when it is safe and prudent to fly helicopters to offshore installations in a harsh oceanic environment.
Motivated by a desire to reduce “boomerang” flights, which are costly and inefficient, we created the high-risk decision support platform to gather and analyse critical data points before providing a quantified probability of a successful landing being possible. All information is provided on an operator-friendly dashboard speeding up the decision-making process from hours to seconds.
This has helped to realise operational efficiencies, by eliminating fuel wastage, hire costs and manhour downtime, but most importantly reducing employee risk by only taking flights that are safe.
With Wood you can be ready for the future, now.
Talk to our team today!