Real-World Decision Testing
Simulation Engine
The Simulation Engine uses a defined Computational Twin (CT) to run simulations that recreate past organisational states and explore likely future scenarios under different assumptions.
It acts as a safe testbed for identifying the best actions before a final decision.
Features
- Historical Playback: Stream historical events through the CT to recreate past states of your organisation.
- Scenario Simulation: Orchestrate predictive AI models to generate probabilistic forecasts of business performance, with adjustable assumptions.
- Decision Optimisation: Use the simulation to identify the best possible decisions.
- Real-time Analysis: Integrate live data for current-state analysis and up-to-the-minute decision support.
Benefits
- Risk mitigation: Test decisions before implementation to avoid costly mistakes.
- Scenario planning: Explore multiple what-if scenarios to understand potential impacts on KPIs, with confidence intervals to quantify risk and uncertainty across scenarios.
- Optimisation capability: Identify the best possible actions across complex decision spaces.
- Learning foundation: Build organisational knowledge through systematic testing, validation and continuous learning.
Frontier Insights: AI-Powered Simulation
In this video, Faculty’s Solutions Director Stephanie Skeet shares how AI-powered simulation in Faculty Frontier™ is helping leaders test scenarios, explore trade-offs, and make better decisions with confidence.
Frontier Insights: AI-Powered Simulation
In this video, Faculty’s Solutions Director Stephanie Skeet shares how AI-powered simulation in Faculty Frontier™ is helping leaders test scenarios, explore trade-offs, and make better decisions with confidence.