How to Perform What‑If Scenario Analysis Using Dashboard Parameters in Bold BI

What‑If analysis enables users to explore different business scenarios by modifying input values and immediately observing their impact on dashboard metrics.
In Bold BI, What‑If analysis can be achieved using Dashboard Parameters combined with Calculated Fields (Expression Columns).
This approach allows users to:

• Simulate growth, reduction, or adjustment scenarios.
• Recalculate metrics dynamically in real time.
• Compare multiple independent scenarios.
• Analyze outcomes without modifying the underlying data source.

Step‑by‑Step Guide

Step 1. Open the dashboard in Bold BI Dashboard Designer

• Sign in to Bold BI and open your existing dashboard.
• Click Edit to launch the Bold BI Dashboard Designer.
  
  

Step 2. Identify suitable What‑If inputs

Before creating parameters, determine what type of user‑driven adjustments your scenario requires.

• Common examples include:

  • Percentage‑based growth or reduction
  • Category‑specific adjustments
  • Scenario‑driven numeric changes
  • Forecast-based simulations

• Assume your dataset contains:

  • A categorical field (for example, Region, Department, or Category)
  • A numeric field representing a base value (for example, Units, Quantity, or Amount)

Step 3. Create dashboard parameters

• While in Dashboard Designer, open the Data Design View by clicking on the edit datasource icon
  
  
• In the Data Design View, locate the Dashboard Parameters icon.
  
  
• Click Add to create a new parameter.
• Create a separate Number-type dashboard parameter for each independent scenario. For example:
  • Northern_Adjustments
  • Central_Adjustments
  • Eastern_Adjustments
  • Western_Adjustments

• These values are interpreted as percentages (for example, 10 represents a 10% increase).

Step 4. Create a calculated field to apply the What‑If logic

• To apply parameter‑driven adjustments, create an expression (calculated) column that recalculates values at row level based on the category and corresponding parameter.
• In the Data design view, locate the Calculated Columns / Expressions section.
  
  
• Click Add (or Create Expression) to open the Expression Designer.
  
  
• Use a conditional expression to apply parameter-driven adjustments based on category values. The following example demonstrates how each region is adjusted independently:

CASE
 WHEN [MarketZone] = 'Northern Hub'
   THEN [BaseUnits] * (1 + (@{{:Northern_Adjustments}} / 100))
 WHEN [MarketZone] = 'Central Hub'
   THEN [BaseUnits] * (1 + (@{{:Central_Adjustments}} / 100))
 WHEN [MarketZone] = 'Eastern Hub'
   THEN [BaseUnits] * (1 + (@{{:Eastern_Adjustments}} / 100))
 WHEN [MarketZone] = 'Western Hub'
   THEN [BaseUnits] * (1 + (@{{:Western_Adjustments}} / 100))
 ELSE [BaseUnits]
END 

• This approach ensures:

  • Adjustments are applied at the row level
  • Aggregations are computed after adjustments
  • Each category responds only to its assigned parameter

Step 5. Bind widgets to the calculated field

• Save the datasource and navigate back to your dashboard designer
• Add or edit KPI, Card, or Chart widgets.
• Use the calculated field (for example, AdjustedUnits) instead of the base numeric column.
• Save the widget configuration.
  
  

Widgets will now recalculate dynamically when parameter values are changed in the dashboard viewer.

Step 6. (Optional) Create dependent calculated metrics

Additional metrics can be derived from the adjusted values. For example, cost‑based calculations:

AdjustedUnits * RatePerUnit 

This allows multiple KPIs or charts to react consistently to What‑If inputs.

Step 7. Publish and validate

• Click on Preview to open the dashboard in viewer mode.
  
  
• In Preview mode, Click on the Parameters icon on the top navigation
  
  
• Modify parameter values and verify that widgets update as expected.
  
  

Limitations

• KPI, Card, and Chart widgets support dashboard parameter recalculation reliably.
• Currently, Grid widgets may briefly reflect updated values and then revert due to refresh behavior.
  This is a known limitation and does not indicate an issue with parameter configuration or expression logic.

Best Practices

• Apply What‑If logic at row level, not on aggregated values
• Use one dashboard parameter per independent adjustment scenario
• Keep parameter names consistent and descriptive
• Prefer charts and KPI widgets for What‑If scenarios

Conclusion

Bold BI supports flexible What‑If analysis using dashboard parameters and expression columns. By applying parameter‑driven logic at row level and referencing parameters using the correct @{ParameterName} syntax, dashboards can support interactive scenario analysis without modifying the underlying data.

Related Articles

• Bold BI – A Basic Walkthrough (Creating a dashboard)
• Advanced Dashboard Interactivity using Parameters (Blog)