
Data is collected on all projects during construction that could enable an automated compliance system, but it’s often stored in silos across the project. Construction teams report their activities to the Construction Manager, who provides an extract to the Environmental Compliance Manager (ECM). The ECM then calculates whether the operations are compliant. By combining construction data in a Common Data Environment, we can apply algorithms that can read reports, undertake calculations and compare the outputs to consent conditions, in real time.
Gathering data centrally and analysing it using machine learning algorithms, provides two additional benefits over and above real time compliance monitoring. Firstly, intelligent systems can learn over time. By comparing construction activities to monitoring data, predictions can be made about whether future activities are likely to be non-compliant. This can also draw in other datasets to adjust predictions based on weather forecasts or other influencing factors. Each day that the system mitigates constructions, the risk of delay avoids upwards of £250,000 per day per vessel.
Secondly, auditing data is more valuable for your investors than it is for your regulators. Once an offshore wind farm is built, the licence to operate the offshore transmission is sold under the OFTO Regime. The transfer value of of Offshore Transmission Ownership (OFTO) ranged between £300 and £500 million per asset in the last round of tenders. If clearly demonstrating environmental compliance improved investor confidence by just 1%, that would create £3 to £5 million, simply by creating a better filing system.
When considered in these terms, the cost of not monitoring and auditing environmental data proactively can be measured in the millions of pounds per day.