Page pattern
Variance / Difference Analysis
Explain the difference between actual and a reference (target, budget, previous year) in full.
- “Why is actual different from target?”
- “Which departments cause the difference?”
- “Is the gap concentrated or spread out?”
Variance / Difference Analysis — clickable example
Shared retail dataset. Every control works; the log shows what Power BI would change.
Gap €-89k (-1%) against target.
Bars: Revenue · vertical marker: Budget
| Rows | Revenue | Budget | vs Budget |
|---|---|---|---|
| €2.4M | €2.5M | -0.9% | |
| €1.7M | €1.7M | -0.7% | |
| €1.7M | €1.7M | -0.8% | |
| €1.4M | €1.4M | -1.4% | |
| €1.2M | €1.2M | -1.7% | |
| Total | €8.4M | €8.5M | -1.0% |
| vs Budget | ||||
|---|---|---|---|---|
| Fresh | €2.4M | €2.5M | €608k | ▼ -0.9% |
| Beverages | €1.7M | €1.7M | €426k | ▼ -0.7% |
| Grocery | €1.7M | €1.7M | €426k | ▼ -0.8% |
| Non-food | €1.4M | €1.4M | €346k | ▼ -1.4% |
| Household | €1.2M | €1.2M | €291k | ▼ -1.7% |
| Total | €8.4M | €8.5M | €2.1M | -1.0% |
- Interact with a slicer, a bar or a navigation button to see the native behaviour described here.
Variance / Actual vs Target — archetype wireframe
[ Variance KPIs ] [ Actual vs target ] [ Variance visual ] [ Contributors ] [ Detail ]
Reading order follows the zones above, top-left to bottom-right.
Components: Cards, Waterfall, Bar/Column charts, Matrix
Hierarchy: Context/control → status/primary answer → explanation/breakdown → detail → next step.
Interaction: Use only interactions that support the page's next analytical step; typical next level: **Root-cause analysis**.
Navigation: Root-cause analysis
Implementation: Compose from the listed native visuals/controls and the standard interaction patterns in this guide; custom visuals are exceptions.