Simulation Tab
The Simulation tab is where Digital Twins become actionable. You've discovered causal relationships, validated model quality—now you can ask "what if?" and get answers backed by causal evidence.
This tab provides access to all simulation types: interventions, optimizations, counterfactuals, explanations, predictions, and forecasts. Each serves a different analytical purpose, but they all leverage the same underlying causal model.
For detailed documentation of each simulation type, see the Simulations guide.
(SCREENSHOT: Simulation tab overview showing simulation type selector and recent runs)
Simulation Types Overview
Intervention
"What happens if we change X?"
Testing policy changes, what-if scenarios
Optimization
"What settings achieve goal Y?"
Finding optimal strategies, resource allocation
Best Action
"What's the minimum change to reach Z?"
Counterfactual reasoning, targeted actions
Explanation
"Why did outcome W happen?"
Root cause analysis, driver identification
Prediction
"What will happen to this case?"
Risk assessment, lead scoring
Forecast
"What will happen over time?"
Trend projection, planning (temporal only)
(SCREENSHOT: Simulation type selector cards with icons)
Creating a New Simulation
Click New Simulation
Select the simulation type
Configure parameters (varies by type)
Click Run
Each type has a dedicated configuration form. See below for type-specific details.
(SCREENSHOT: New simulation dialog with type selection)
Intervention Simulations
Test what happens when you change one or more variables.
Configuration:
Select variables to intervene on – Which variables are you changing?
Set intervention values – What are the new values?
Define conditions (optional) – Apply only to certain segments
Define metrics – SQL queries to measure outcomes
Example:
"What happens if we increase marketing_spend by 20%?"
Results:
Baseline vs. intervention comparison
Effect on each metric
Confidence intervals
Monte Carlo distributions
(SCREENSHOT: Intervention configuration form and results)
Optimization Simulations
Find the best variable settings to achieve objectives.
Configuration:
Define objectives – What to maximize or minimize
Select decision variables – What can the optimizer change?
Set constraints – Limits that must be respected
Example:
"Find the marketing mix that maximizes conversions with a $100K budget"
Results:
Optimal values for each decision variable
Expected outcome at optimum
Constraint satisfaction status
(SCREENSHOT: Optimization configuration and results showing optimal settings)
Best Action (Counterfactual)
Find the minimum changes needed to achieve a desired outcome.
Configuration:
Provide sample records – Specific cases to analyze
Set target outcome – What result do you want?
Configure constraints – What can/can't change?
Set max changes – Limit recommendation complexity
Example:
"What's the smallest discount needed to convert this hesitant customer?"
Results:
Recommended changes for each sample
Expected success probability
Comparison of before/after
(SCREENSHOT: Best Action configuration with sample records and recommendations)
Explanation Simulations
Understand causal drivers behind outcomes.
Three Modes:
Directional – How does A affect B specifically?
Discovery – What influences outcome B?
Impact – What does variable A affect?
Configuration:
Select mode
Choose source and/or target variables
Optionally filter by segment
Results:
Causal paths with contribution weights
Effect sizes for each driver
Segmented breakdown if applicable
(SCREENSHOT: Explanation results showing causal driver breakdown)
Prediction Simulations
Generate predictions for specific cases.
Configuration:
Enter input values – Known variable values
Select targets – What to predict
Results:
Predicted value for each target
Confidence intervals
Full probability distribution
(SCREENSHOT: Prediction input form and results with confidence intervals)
Forecast Simulations (Temporal Only)
Project variables forward in time.
Configuration:
Select target variables – What to forecast
Set forecast horizon – How far ahead
Choose starting point – When to begin forecast
Set confidence level – Width of uncertainty bands
Results:
Time series projections
Confidence bands
Trend visualization
(SCREENSHOT: Forecast results showing time series with confidence bands)
Natural Language Input
For Intervention and Optimization, you can describe scenarios in plain language:
"What happens if we raise prices by 10% for premium customers?"
RootCause.ai translates this into a structured simulation. Review the generated configuration and adjust if needed.
(SCREENSHOT: Natural language input field with generated configuration below)
Simulation Runs History
The tab maintains a history of all simulation runs:
Runs List
Shows all past simulations with:
Type
Configuration summary
Run date
Status
Viewing Past Results
Click any run to see its full results without re-running.
Comparing Runs
Select multiple runs to compare results side-by-side.
(SCREENSHOT: Runs list showing simulation history with status indicators)
Running Across Versions
Test simulations on multiple Digital Twin versions:
Select versions from the dropdown
Run the simulation
Results show side-by-side by version
Useful for:
Validating that model changes don't alter conclusions
Comparing predictions across model iterations
Testing model stability
(SCREENSHOT: Version selector for cross-version simulation)
Interpreting Results
Confidence Intervals
All results include uncertainty estimates:
Narrow intervals = high confidence
Wide intervals = more uncertainty
Consider intervals when making decisions
Monte Carlo Sampling
Simulations run thousands of scenarios internally:
Results are distributions, not point estimates
You see the range of what could happen
Captures model uncertainty
Baseline Comparison
Intervention and optimization results compare against baseline:
Shows marginal effect of your action
Helps quantify the value of intervention
Best Practices
Start Simple
Test single interventions before combining multiple changes.
Use Realistic Values
Stay within your data's range. Extreme interventions may be unreliable.
Verify with Domain Experts
Share results before acting. Do they make business sense?
Document Important Simulations
Save or export results for audit trail and reproducibility.
Next Steps
Share findings in Reports
Use RootCause Assistant to explore via conversation
Refine model in Config Tab if results suggest issues
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