Traditional assurance typically uses historical data to describe past events. This project aims to put "Prescriptive Assurance" into practice – a risk-based assurance process that goes beyond this ‘descriptive’ approach to diagnosing root causes, anticipating related risks, and prescribing fixes.
Building on Assurance Services International’s risk-based assurance model and certification body performance monitoring, the project will integrate external data sources, AI technology, and statistical analytics tools into a centralised alert system. This system will predict risks and recommend targeted measures to mitigate them. Deliverables include a proof-of-concept and guidance for applying the framework across sustainability systems; an integrated alert platform with dashboards and geospatial analytics, and ‘how-to’ guidance on building the alert system.
Ultimately, this approach aims to make conformance more efficient, provide scheme owners with feedback to design more relevant standards, and increase the impact of sustainability systems.
