What-If Parameters for Scenario Analysis
Enable dynamic what-if scenario analysis in Power BI with user-adjustable parameters. Build sliders for financial modeling, forecasting, and sensitivity testing.
What-if parameters transform static Power BI reports into dynamic scenario modeling tools. Instead of showing only historical data, what-if parameters let business users adjust assumptions—price increases, growth rates, discount percentages, headcount changes—and instantly see how those changes affect KPIs and projections. This capability bridges the gap between descriptive analytics ("what happened") and prescriptive analytics ("what should we do").
How What-If Parameters Work
A what-if parameter creates three things in your Power BI model:
- A disconnected table containing a range of values (e.g., -20%, -15%, -10%, ..., 15%, 20%)
- A slicer bound to this table, allowing users to select a value
- A measure that returns the currently selected value
The parameter table has no relationships to other tables—it is "disconnected." Your DAX measures reference the parameter's value measure to adjust calculations. When a user moves the slicer, the value changes, measures recalculate, and all dependent visuals update instantly.
Creating What-If Parameters
In Power BI Desktop: Modeling tab > New Parameter > What-If.
Configure the parameter:
| Setting | Description | Example | |---|---|---| | Name | Descriptive label | Price Increase % | | Data Type | Decimal or Whole Number | Decimal Number | | Minimum | Lowest allowed value | -0.20 (-20%) | | Maximum | Highest allowed value | 0.30 (30%) | | Increment | Step between values | 0.01 (1%) | | Default | Starting value | 0.00 (0%) |
Power BI generates the parameter table and slicer automatically. Customize the slicer format (slider vs dropdown) and label in the visual formatting pane.
Building Scenario Measures
The real value comes from DAX measures that reference the parameter:
Simple Price Scenario: Projected Revenue equals your Actual Revenue multiplied by (1 + the Price Increase Value). When the user selects 10%, projected revenue shows 110% of actual.
Margin Impact: Projected Margin equals (Actual Revenue times (1 + Price Increase Value)) minus Cost. The price increase flows through to margin while costs remain unchanged, showing the profit impact of pricing decisions.
Break-Even Analysis: Break-Even Point equals Fixed Costs divided by ((Actual Revenue times (1 + Price Increase Value)) divided by Units minus Variable Cost per Unit). Users slide the price parameter to find the point where revenue covers all costs.
Compound Scenarios: Combine multiple parameters for multi-variable analysis. Revenue Scenario equals Actual Revenue times (1 + Price Increase Value) times (1 + Volume Growth Value). Users adjust both price and volume independently to model combined effects.
Financial Modeling Scenarios
Pricing Strategy Create a parameter ranging from -20% to +30% in 1% increments. Build measures for: projected revenue, projected margin, projected market share (inverse relationship with price), and projected profit. Visualize the trade-off between price increases and volume loss.
Cost Sensitivity Model the impact of raw material cost changes on product margins. Parameter range: -15% to +40% (costs rarely decrease dramatically). Measures show: unit margin at different cost levels, break-even volume changes, and which products become unprofitable at various cost points.
Growth Rate Planning Model different growth scenarios for budgeting and resource planning. Parameter range: 0% to 50% annual growth in 5% increments. Measures show: projected headcount needs, infrastructure costs, revenue projections, and cash flow impact. Visual shows when the organization hits capacity constraints at different growth rates.
Sales Forecasting Scenarios
Conversion Rate Modeling Sales teams want to know: "If we improve our conversion rate from 15% to 20%, what happens to revenue?" Create a conversion rate parameter, multiply pipeline value by the selected rate, and show projected closed deals, revenue, and commission impact.
Discount Impact Model the revenue impact of different discount levels. Parameter: 0% to 40% discount. Measures: total revenue at discount level, margin erosion, required volume increase to maintain margin, and net profit. This helps sales leaders set discount authority limits with data-driven reasoning.
Seasonal Adjustment Create a seasonality factor parameter that adjusts forecasts based on expected seasonal variation. Users can model "what if this holiday season is 10% stronger/weaker than average" to set inventory and staffing levels.
Capacity and Resource Planning
Headcount Scenarios Parameter: additional headcount (0 to 50 people). Measures: total salary cost, revenue per employee, output projection based on historical productivity ratios, and the number of months until new hires reach full productivity. Helps HR and finance model hiring plans.
Utilization Targets Parameter: target utilization rate (60% to 95%). Measures: revenue at utilization level, billable hours required, available capacity, and overtime probability. Essential for professional services firms managing consultant utilization.
Advanced Multi-Parameter Dashboards
Build a scenario planning dashboard with 3-4 parameters on a single page:
- Revenue Growth % (0% to 30%)
- COGS Increase % (-5% to 20%)
- Headcount Growth (0 to 25 people)
- Discount Rate % (0% to 15%)
Display a scenario summary card showing projected P&L under the selected assumptions. Add a sensitivity table that shows margin at different combinations of growth and cost parameters. Include a comparison visual showing "Current Plan" vs "Selected Scenario" side by side.
Best Practices
- Set defaults to the most likely scenario (base case), not zero
- Use clear labels with units (%, $, count) so users understand what they are adjusting
- Add conditional formatting that changes color when scenarios become unrealistic (negative margin, impossible utilization)
- Include a "Reset to Base Case" bookmark button so users can quickly return to default assumptions
- Validate calculations at extreme values—ensure measures do not produce errors or nonsensical results at parameter boundaries
Related Resources
Frequently Asked Questions
What are common use cases for what-if parameters?
Common uses include financial modeling (price changes, cost assumptions), sales forecasting (growth rates, conversion rates), capacity planning (headcount, utilization), and sensitivity analysis for business decisions.
Can I use multiple what-if parameters together?
Yes, you can create multiple parameters and reference them in the same measures. This enables multi-variable scenario modeling, like adjusting both price and volume simultaneously.