Simulation Types

A simulation uses a Digital Twin, which is RootCause's runnable causal model of your business, to answer a specific kind of question. Each simulation type runs on the same underlying twin but is configured for a different purpose: predicting outcomes, testing interventions, finding optimal inputs, diagnosing anomalies, and more.

This section has one page per simulation type, covering when to use it, how to set it up, and how to read the result. For the workflow that produces a Digital Twin in the first place, see Step 5: Build Digital Twin.

The seven types

Static Digital Twins support seven simulation types.

#	Type	Question it answers
1	Prediction	What outcome is most likely for a specific input?
2	Intervention	What happens if we change variable X?
3	Optimization	What combination of inputs best achieves our goal?
4	Best Action	What is the minimum change needed to reach a target outcome?
5	Explanation	What drives an outcome, and what does a cause influence?
6	Root Cause Analysis	What caused this specific observed outcome?
7	Anomaly Scan & Diagnosis	Which records are anomalous, and why?

Temporal Digital Twins — those built on time-series data — support a parallel family of time-aware simulations: Forecast, a temporal counterpart to each static type, and the temporal-only Causal Health Monitor. Panel (multi-environment) twins get per-environment Panel variants of the same family. See Temporal Simulations.